Lucky Lotto Numbers

Combinatorics

Select 5 unique numbers from 1 to 50, features of this random picker.

  • Lets you pick 5 numbers between 1 and 50.
  • Pick unique numbers or allow duplicates.
  • Select odd only, even only, half odd and half even or custom number of odd/even.
  • Generate numbers sorted in ascending order or unsorted.
  • Separate numbers by space, comma, new line or no-space.
  • Download the numbers or copy them to clipboard
  • Click on Start to engage the random number spinner. While spinning, you have three optons: 1) Press "Stop" to stop all the numbers 2) Press "One" to stop the numbers manually one by one, or 3) Press "Zoom" to let the spinner come to a stop slowly revealing all your numbers.

Magic Filters

Display font, add/roll dice, random numbers, number converters, number formats, number lists.

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Random Number Generator

This version of the generator creates a random integer. It can deal with very large integers up to a few thousand digits.

Comprehensive Version

This version of the generator can create one or many random integers or decimals. It can deal with very large numbers with up to 999 digits of precision.

A random number is a number chosen from a pool of limited or unlimited numbers that has no discernible pattern for prediction. The pool of numbers is almost always independent from each other. However, the pool of numbers may follow a specific distribution. For example, the height of the students in a school tends to follow a normal distribution around the median height. If the height of a student is picked at random, the picked number has a higher chance to be closer to the median height than being classified as very tall or very short. The random number generators above assume that the numbers generated are independent of each other, and will be evenly spread across the whole range of possible values.

A random number generator, like the ones above, is a device that can generate one or many random numbers within a defined scope. Random number generators can be hardware based or pseudo-random number generators. Hardware based random-number generators can involve the use of a dice, a coin for flipping, or many other devices.

A pseudo-random number generator is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. Computer based random number generators are almost always pseudo-random number generators. Yet, the numbers generated by pseudo-random number generators are not truly random. Likewise, our generators above are also pseudo-random number generators. The random numbers generated are sufficient for most applications yet they should not be used for cryptographic purposes. True random numbers are based on physical phenomena such as atmospheric noise, thermal noise, and other quantum phenomena. Methods that generate true random numbers also involve compensating for potential biases caused by the measurement process.

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Random Number Generator

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Calculator Use

Generate one or more random numbers in your custom range from 0 to 10,000. Generate positive or negative random numbers with repeats or no repeats.

About Random Number Generators

There are two main types of random number generators: pseudo-random and true random.

A pseudo-random number generator (PRNG) is typically programmed using a randomizing math function to select a "random" number within a set range. These random number generators are pseudo-random because the computer program or algorithm may have unintended selection bias. In other words, randomness from a computer program is not necessarily an organic, truly random event.

A true random number generator (TRNG) relies on randomness from a physical event that is external to the computer and its operating system. Examples of such events are blips in atmospheric noise, or points at which a radioactive material decays. A true random number generator receives information from these types of unpredictable events to produce a truly random number.

This calculator uses a randomizing computer program to produce random numbers, so it is a pseudo-random number generator.

How to Generate Random Numbers

  • What is your range? Set a minimum number and a maximum number. The random number(s) generated are selected from your range of numbers, with the min and max numbers included.
  • How many numbers? Specify how many random numbers to generate.
  • Allow repeats? If you choose No your random numbers will be unique and there is no chance of getting a duplicate number. If you choose Yes the random number generator may produce a duplicate number in your set of numbers.
  • Sort numbers? You can decide not to sort your random numbers. You can also order your random numbers ascending, lowest to highest or descending, highest to lowest.

Do you need to include random numbers and letters in a random character set? See the CalculatorSoup ® Random Number and Letter Set Generator .

Example: Generate a Random Number to Use as a PIN .

To generate a 6-digit PIN with or without duplicate digits choose the following settings:

  • Generate 6 numbers
  • Allow repeats = yes or no
  • Sort numbers = Do not sort

Do it: Generate a 6 digit PIN without duplicates

Example: Randomize a Set of Numbers

Say you have a group of 10 people represented by the numbers 1 to 10. You want to shuffle them into a random order of selection for an event.

Choose the following settings to randomize order of selection:

  • Generate 10 numbers
  • Allow repeats = no

Do it: Randomize the order of a set of numbers, 1 to 10

Example: Randomly Choose One Number From a Range of Numbers

Say you want randomly select one number from 1 to 10, like drawing a number out of a hat.

Choose the following settings:

  • Generate 1 number

Do it: Random number generator 1 to 10

Also try: Random number generator 1 to 100

Example: Lottery Number Generator

You want to generate numbers for lottery tickets. You need to choose 5 numbers from a pool of 1 to 49 without duplicates.

Choose the following settings in the random number generator:

  • Generate 5 numbers
  • Allow Duplicates = no
  • Sort Numbers = low to high

Do it: Generate 5 lottery numbers from a range of 1 to 49

Cite this content, page or calculator as:

Furey, Edward " Random Number Generator " at https://www.calculatorsoup.com/calculators/statistics/random-number-generator.php from CalculatorSoup, https://www.calculatorsoup.com - Online Calculators

Last updated: September 19, 2023

Random 5 Digit Number Generator

"numerical mastery at your fingertips" generate unique 5-digit numbers with ease.

Dive into the world of numbers with our Random 5 Digit Number Generator. Whether you're in need of random codes, identifiers, or just aiming for pure randomness, this tool effortlessly creates a set of unique 5-digit numbers tailored to your requirements.

Creating Numbers Has Never Been This Easy!

  • Journey to the Numeric Hub: Start by navigating to Random 5 Digit Number Generator .
  • Specify Your Need: Input the quantity of 5-digit numbers you wish to generate.
  • Press 'Generate': A simple click will unravel a series of unique 5-digit numbers exclusively for you.

Our system utilizes advanced algorithms to ensure that each number generated is distinct from the rest.

Why Use a Random 5 Digit Number Generator?

  • Secure Codes: Perfect for generating random access codes, verification numbers, or PINs.
  • Educational Purposes: Educators can use this to create practice math problems or tests.
  • Unique Identifiers: Useful for businesses in need of product IDs or internal coding systems.
  • Random Draws or Contests: Employ it to randomly select winners or participants.

How random are these 5-digit numbers? Our generator employs sophisticated algorithms, guaranteeing a high level of randomness and ensuring each number is distinct.

Is there a cap on the number of 5-digit numbers I can generate at once? While our tool can handle large requests, we recommend generating numbers in manageable batches for optimum performance.

Can I generate numbers for other digit lengths using this tool? This specific tool is optimized for 5-digit numbers. However, we have other tools designed for different digit lengths on our platform.

Jump into a realm where numbers rule supreme. With the Random 5 Digit Number Generator , you're never more than a click away from obtaining the exact set of numbers you need. Unlock the power of randomness and let numbers become an integral part of your toolkit. Happy generating!

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Random Number Generator

This online random number generator allows you to generate random numbers within a specific range. To use the generator, follow these four simple steps:

  • Enter the lower and upper bounds of the number range
  • Enter the count of numbers to generate
  • Select the type of numbers you wish to generate
  • Click the "Generate" button to create an array of random numbers.

Lower Bound:

Upper Bound:

No. of Randoms:

Type of Number: Any Integer Even Odd Prime Multiple of Power of 2 Perfect Square Fibonacci Number

Allow Duplicates? Yes No

Decimal Precision: 0 1 2 3 4 5 6 7 8 9

Random number generators are typically used when developing games of chance simulations or within statistical analyses. For instance, online poker games use a random number generator to deal the shuffled cards in a random manner. The random functions that are typically incorporated into contemporary programming languages, such as JavaScript, C++, Java, and PHP are pseudorandom number generators, which are also referred to as PRNGs. Pseudorandom number sequences take the form of periodic sequences that span exceptionally large periods and, as such, replicate the behavior of genuinely random sequences.

You would need some form of external hardware that can detect randomness in physical processes to generate genuinely random numbers. For instance, many generators can detect noise in sound, light, temperature, or other quantum phenomena. These generators subsequently use these signals to construct a sequence of absolutely random numbers. Some producers sell entropy keys that can be used in combination with a USB drive. Some of the more professional online gaming websites use hardware-based RNGs to avoid a situation in which players are able to predict what cards they will be dealt.

You may also be interested in our Normal Distribution Generator or Lottery Number Generator

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Number Generator

The random number generator provides a set of random numbers according to user-specified options such as range, repeat, and sort.

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Random Number Generator

Random Numbers

48, 9, 49, 11, 17, 22, 16, 37, 45, 41, 4, 36, 43, 10, 28, 27, 47, 25, 21, 33

There was an error with your calculation.

Table of Contents

The use of random number generators, the random and a non-random sequence difference, the types of random number generators.

  • Google's Generator

The Linear Congruent Method

Vacuum quantum fluctuations, carbon nanotube generator, cubes and the electronic frontier foundation (eff), a quantum random number generator from a nokia smartphone.

A random number generator is a process of getting a random number every time it is needed, without the ability to define a pattern from previously generated numbers. This number can be generated either by an algorithm or a hardware device.

Generating random numbers is needed for various tasks, from computer games to common applications. For example, the system uses a random number generator to display a random banner or a random ad unit on a website. In cryptography, random numbers are also used to make a unique cipher or key.

Random number generation is used to generate numbers or text for captcha, encryption, generating salt for storing passwords, a password generator, an order of cards in an online casino, decision-making, sampling, and simulation.

The random number generator algorithm is often used in video games. Even if you play at the same level in a game, it will not be precisely the same every time you try to complete a mission. Maybe the differences will not be seen in the location or mission. Still, they will be seen in the number of enemies approaching and the areas where they appear, the climate changes, and the various obstacles encountered. This makes the game more exciting.

Let there be a sequence of numbers: 1 , 2 , 3 , 4 , 5 . Is it random?

A random variable is a variable that takes on one of some values as a result of a trial. And you cannot accurately predict the occurrence of a particular value before it appears.

Let's say that the given numbers were obtained by typing on one of the top rows of the keyboard. In this case, it turns out that this combination is not random because, after 5, the following number, 6, can be predicted with high probability.

The sequence will be random only if there is no dependence between symbols.

The basic condition, which is extremely important for the correct and fair principle of the random number generator, is an absolutely equal probability of any possible number that could fall out in this system. This indicates complete independence of the randomness factor and independence of what other numbers fell out before or after the random number.

For example, suppose you roll a six-sided die for the first time. In that case, you can have absolutely any number from 1 to 6 falling out with the same probability. Regardless of your number, you can roll the dice again with the same chance of getting the same number on the second, hundredth, or thousandth roll.

The sequence of digits in the number Pi appears to be non-repetitive, and to many, it might seem random. Suppose our hypothetical generator relies on the bit representation of Pi, beginning from an undisclosed point. Such a generator might be unpredictable in many contexts, potentially passing certain tests for randomness. However, relying on Pi for cryptographic purposes poses risks. If an adversary determines the specific segment of Pi being used, they can predict both preceding and following segments, compromising the security of the system.

The U.S. National Institute of Standards and Technology proposed the "Statistical Test Package for Random and Pseudorandom Number Generators for Cryptographic Applications." It includes 15 statistical tests whose purpose is to determine the measure of randomness of bits generated by either hardware or software generators.

There are two types of random number generators (RNG): true random number generators (TRNG) and pseudo random number generators (PRNG). TRNGs use physical phenomena to generate numbers, while PRNGs use mathematical algorithms.

A true random number generator algorithm is created with a hardware device that uses tiny physical processes to generate random numbers, namely entropy. Entropy is pure, unfiltered chaos.

True random number generators use physical phenomena such as:

  • radioactivity,
  • thermal noise,
  • electromagnetic noise,
  • quantum mechanics, and others.

A true RNG is commonly used in security-oriented systems worldwide and some forms of encryption.

Random number generators use entropy sources to accumulate entropy and obtain the initial value (seed) needed by random number generators.

The pseudorandom number generator algorithm is used in areas with no security concerns. Randomness helps to avoid repetition and make the process more attractive to the end user. Implementing the technology of pseudorandom number generators is cheaper and faster because it does not require hardware and can easily be built into program code. Although the process is not entirely random and is determined based on an algorithm, it is more suitable for games and programs.

The PRNG uses a single initial value, from which its pseudo-randomness follows. At the same time, the true random number generator always generates a random number by having a high-quality random value provided at the beginning by various sources of entropy.

Pseudorandom number generation has its drawbacks. They work because they are random to the untrained eye. However, suppose you knew the initial value for a particular sequence of PRNGs. In that case, you could predict which numbers would be next.

Speed-playing video game enthusiasts often exploit this vulnerability—they call it manipulation of the PRNG. They make the game run predictably so they can pass it as quickly as possible. Fortunately, it does not entail critical problems.

But there are times when predicting random numbers is much more critical. For example, when creating security keys.

If the attacker figures out the initial value used to create RSA keys in TLS certificates, he could potentially decrypt network traffic. This means he can get passwords and other personal information sent over the Internet.

In these situations, a more secure way to get random numbers, i.e., a true random number generator, is needed.

Google's Generator

Google has its own tool for generating random numbers based on JavaScript. This tool can be useful when playing games with friends and family. You can find this generator if you type in the Google search query "random number generator."

One of the most popular algorithms for pseudorandom number generators is the Linear Congruent Method. It is used in simple cases and has no cryptographic strength. Derrick Henry Lehmer proposed the linear congruent method in 1949.

To implement the generation of numbers by this method, we need to pick four numbers:

m > 0 , modulo

0 ≤ a ≤ m , the multiplier

0 ≤ c ≤ m , the increment

0 ≤ X₀ ≤ m , the initial number

The sequence of random numbers itself is generated using the formula:

Xₙ₊₁ = (aXₙ + c) mod m

It is worth noting that this method depends on the choice of parameters.

For example, for the following set:

X₀ = 3, a = 4, c = 5, m = 6

we get a short repetitive sequence of

3, 5, 1, 3, 5, 1

which does not look random.

But it's worth changing the parameters to something else:

X₀ = 2, a = 85, c = 507, m = 1356

And the scatter of results becomes more unpredictable. You must choose the numbers for this algorithm with special care.

2, 677, 1100, 443, 194, 725, 1112, 107, 110, 365, 344, 1271, 62, 353, 680, 1355, 422, 1121, 872, 47, 434, 785, 788, 1043, 1022, 593, 740, 1031, 2, 677, 1100, 443, 194, 725, 1112, 107, 110, 365, 344, 1271, 62, 353, 680, 1355, 422, 1121, 872, 47, 434, 785, 788, 1043, 1022, 593, 740, 1031, 2, 677, 1100, 443, 194, 725, 1112, 107, 110, 365...

Although the linear congruent method generates a statistically good pseudorandom number sequence, it is not cryptographically robust. Generators based on the linear congruent method are predictable, so you cannot use them in cryptography.

Linear congruent method generators were first cracked by Jim Reeds in 1977 and then by Joan Boyar in 1982. She also managed to break quadratic and cubic generators. Thus, they proved the uselessness of generators based on congruent methods for cryptography. However, generators based on the linear congruent method retain their usefulness for non-cryptographic applications, for example, for simulations. They are efficient and show good statistical performance in most empirical tests.

Modern Hardware Random Number Generators

The randomness effect in the device depends on the quantum physical process of photon emission in semiconductors and the subsequent detection of individual photons. In this process, photons are detected randomly, independently of each other, and the timing information of the detected photons is used to generate bits.

CloudFlare's San Francisco office houses random number generators called "lava lamps". Such a lamp is a glass vessel filled with transparent oil and translucent paraffin. Paraffin is slightly heavier than oil, but when heated slightly, it becomes lighter and floats up.

The movement of the liquids is monitored by several cameras that take snapshots. The snapshots are converted into numbers, from which encryption keys are then generated.

The other two CloudFlare offices use different ways to get random values. In London, a camera captures the movements of three chaotic pendulums. In Singapore is used a Geiger counter that measures the radioactive decay of a small piece of uranium. In the latter case, uranium is used as a "data source" because radioactive radiation is characterized by the randomness of each decay act.

HotBits is a site that provides true random numbers generated by a Geiger counter that registers ionizing radiation to everyone. You fill out a request form on the site specifying the number of random bytes and choose your preferred method of obtaining the data. Once the random numbers are provided to the customer, they are immediately removed from the system.

Contrary to its name ("vacuus"-empty), the vacuum cannot be considered empty. Under the Heisenberg uncertainty principle, virtual particles are born and die unceasingly.

Canadian physicists have designed a fast and structurally simple random number generator based on vacuum fluctuations. The generator consists of a pulsed laser with a high frequency of radiation, a medium with a high refractive index (diamond), and a detector. Passing through the diamond, each pulse on the sensor shows different characteristics depending on the vacuum field fluctuations encountered on the photons' path.

In the spectrum of the scattered radiation, spectral lines appear. Because of the unpredictability of the vacuum fluctuations, these lines differ in unpredictable ways each time.

This method combines compactness with generated thermal noise.

The researchers built a random number generator from a static random access memory cell printed with special inks containing semiconducting carbon nanotubes. The memory cell uses thermal noise fluctuations to generate random bits.

The carbon nanotube generator can be printed on flexible plastic substrates, allowing it to be integrated into tiny, flexible electronics devices, wearable sensors, disposable labels, and smart clothing items.

The company has proposed a simple way to create secure passwords using a physical random number generator. It is based on dice.

For example, you roll five dice at a time and write down the resulting numbers. The dice are arranged from left to right as follows: 63131. Next, you open a long list of words on the EFF website to find the corresponding word next to 63131. That word is "turbofan."

You can repeat this procedure several times. For example, five times. You may end up with a phrase of five words. Let's say, "turbofan purge unfitting try pruning." If you know how to use the rules of mnemonics, you can memorize phrases like these.

In 2014, the University of Geneva created a QRNG device that used the camera of the Nokia N9 smartphone.

The smartphone camera counted the number of photons hitting each pixel. The light source was a standard LED. Each pixel in the 8 MP camera detected about 400 photons in a short time. The total number of photons at all pixels was then converted into a sequence of random numbers.

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Coming soon, coming later, random number generator.

Quickly generate a list of random numbers in your browser. To get your list, just specify the minimum and maximum values, and how many numbers you need in the options below, and this utility will generate that many random numbers. Created by developers from team Browserling .

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Integers or Fractions

Random number bounds, quantity and delimiter, what is a random number generator.

This is an online browser-based utility for generating sequences of random numbers. You can generate any quantity of random numbers from a certain interval. You can specify the lower bound of the interval (that is, all random numbers will be greater than or equal to this value) and the upper bound (that is, all random numbers will be less than or equal to this value). If you select the list-of-random-integers function, each number will be an integer but if you activate the list-of-random-fractions function, each number will be a floating point number. In this case, you can also specify the number of digits in the decimal part. The output list of random numbers can be customized by separating numbers in the list by an arbitrary character. That's numberwang!

Random number generator examples

Random positive numbers.

In this example, a list of ten random whole numbers is generated. By changing the random number range bounds we mandate that all random numbers must be greater than or equal to 1 and less than or equal to 10000.

Random Negative Numbers

This example generates a sequence of twenty negative random integers. All numbers are in the range from -200 to -100 and separated from each other by the comma symbol.

Random Decimal Fractions

This example generates random decimal numbers with three digits in the fractional part. We set the lower bound to -5 and upper bound to 5, which means all decimal numbers will be picked from the interval [-5, 5]. We generate 30 fractions and put the hash character between them.

Pro tips Master online number tools

You can pass options to this tool using their codes as query arguments and it will automatically compute output. To get the code of an option, just hover over its icon. Here's how to type it in your browser's address bar. Click to try!

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Quickly create a matrix with random numbers as its elements.

Quickly create a random row or column vector.

Quickly exchange rows and columns of a matrix.

Quickly find the inverse matrix of any square matrix.

Quickly find the determinant of any square matrix.

Quickly calculate any number of digits of number π.

Quickly generate the specified number of Euler constant's digits.

Quickly generate any number of golden ratio digits.

Quickly generate numbers of say what you see sequence.

Quickly calculate numbers of Fibonacci sequence.

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Quickly generate Fibonacci-like series with custom start values.

Quickly calculate members of a linear recurrence series.

Quickly create a sequence of prime numbers.

Quickly check if the given number is a prime.

Quickly compute all prime factors of a number.

Quickly compute all divisors of a number.

Quickly calculate the GCD of two or more numbers.

Quickly calculate the LCM of two or more numbers.

Quickly create a list of increasing or decreasing integers.

Quickly create a sequence of even numbers.

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Quickly create a list of squares.

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Quickly generate a series of numbers in the form 10^n.

Quickly choose one or more numbers from a list of numbers.

Quickly round one or more numbers to the given accuracy.

Quickly sort numbers in ascending or descending order.

Quickly sort number's digits in ascending or descending order.

Quickly randomize the order of digits in a number.

Quickly filter numbers according to certain criteria.

Quickly add up all the numbers in the given list and find their sum.

Quickly multiply all the numbers together and find their product.

Quickly add up all the digits of the given numbers.

Quickly multiply all the digits of the given numbers.

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Quickly find the largest number in a number sequence.

Quickly find the smallest number in a number sequence.

Quickly create a diagonal matrix with ones on the main diagonal.

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Quickly convert spelled numbers to regular numbers.

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Quickly express a number in the form 10^x.

Quickly convert base 10 numbers to base -10.

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Quickly convert simple fractions to pretty Unicode fractions.

Quickly add digits to a number so that it becomes a palindrome.

Quickly test if the given numbers are palindromes.

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randomly generate 5 numbers

Create a list of numberwang numbers.

Create a list of neat looking numbers.

Visualize a number by drawing its digits as a color gradient.

Create a matrix of numbers with rows and cols having same sum.

Given numbers and a grammar, recursively rewrite them.

Create a number from the mantissa, base, and exponent.

Show how a fp number is represented in a computer.

Convert a number to the a×10<sup>b</sup> form.

Convert a number in scientific notation to a regular number.

Create a list of unary numbers (1, 11, 111, 1111, …).

Create a list of alphabetic numbers (a, b, c, …, z, aa, ab, …).

Create a list of Roman numbers (i, ii, iii, iv, v…).

Create a list of Braille numbers (⠂, ⠆, ⠒, ⠲, ⠢, …).

Create a list of random binary numbers.

Create a list of random octal numbers.

Create a list of random decimal numbers.

Create a list of random hexadecimal numbers.

Calculate a cumulative sum of a list of numbers.

Calculate a cumulative difference of a list of numbers.

Calculate a cumulative product of a list of numbers.

Divide two numbers and find their quotient.

Divide the digits of the given number.

Find the factorial of a number.

Find the average of multiple numbers.

Find the mean of multiple numbers.

Find the mode of multiple numbers.

Create one or more anagrams of a number.

Create a list of digit bigrams from a number.

Create a list of digit trigrams from a number.

Create a list of digit ngrams from a number.

Create a list of polynomial progression numbers.

Create a list of metric prefixes.

Report how many digits appear how many times.

Convert a cardinal number to an ordinal number.

Convert an ordinal number to a cardinal number.

Convert Arabic numerals to Roman numerals.

Convert Roman Numerals to Arabic numerals.

Calculate a series of extended Fibonacci numbers.

Find numbers that are both Fibonacci numbers and primes.

Check if a number is a Fibonacci number.

Check if a number is both a Fibonacci number and a prime.

Create a sequence of Fibonacci words.

Create a sequence of Tribonacci words.

Create a sequence of Tetranacci words.

Create a sequence of Pentanacci words.

Calculate a series of extended Lucas numbers.

Check if a number is both a Lucas number and a prime.

Calculate a sequence of Moser-Bruijn numbers.

Calculate a sequence of Oldenburger-Kolakoski numbers.

Calculate a sequence of Stanley numbers.

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Calculate members of Thue-Morse number series.

Create a list of perfect numbers.

Create a list of almost perfect numbers.

Calculate a sequence of abundant numbers.

Calculate a sequence of deficient numbers.

Generate a list of paperfolding sequence numbers.

Create a list of numbers that are not prime.

Generate an LCD display that shows the given number.

Generate a table of numbers.

Check if the given number is a perfect number.

Check if the given number is an abundant number.

Check if the given number is a deficient number.

Find the modulus of a number.

Group together digits of a number.

Create a list of digits from a number.

Apply sprintf or printf function to numbers.

Let Zalgo destroy your numbers.

Repeat a number multiple times.

Create a mirror copy of a number.

Add zeros to a number.

Add a padding of custom symbols to a number.

Reverse the order of digits of a number.

Cyclically rotate digits of a number to the left or right.

Add one to the given number.

Add one to every digit in a number.

Subtract one from the given number.

Subtract one from every digit in a number.

Discover patterns in sequences of numbers.

Find how often numeric values occur.

Find x% of a number.

Create numbers of arbitrary length and properties.

Print the Googol/Google number, which is 10<sup>100</sup>.

Create a list of big numbers.

Create a list of small numbers.

Create a list of natural numbers.

Create a list of rational numbers.

Create a series of numbers where all terms are the same.

Create a sequence of real numbers.

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Create a sequence of binary numbers.

Create a sequence of number pairs.

Create a sequence of number triples.

Create a sequence of number n-tuples.

Create a number with not that many digits.

Create a number with many digits.

Interweave two or more number digit-by-digit.

Rewrite a number in the decimal representation.

Convert a fraction to a decimal number.

Convert a decimal number to a fraction.

Convert a base two number to base eight number.

Convert a base two number to base ten number.

Convert a base two number to base sixteen number.

Convert a base eight number to base two number.

Convert a base eight number to base ten number.

Convert a base eight number to base sixteen number.

Convert a base ten number to base two number.

Convert a base ten number to base eight number.

Convert a base ten number to base sixteen number.

Convert a base sixteen number to base two number.

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Convert a base sixteen number to base ten number.

Convert any number in any base to any other base.

Change the significand of a number.

Change the power of a number.

Replace digits in a number with alphabet letters.

Form a spiral from the digits of a number.

Form a circle from the digits of a number.

Form a tree from the given numbers.

Form a tree from the digits of a number.

Remove the decimal separator from a decimal number.

Modify numbers so they are almost the same but have errors.

Generate various number typos.

Write numbers in a different font.

Write numbers in a bold font.

Write numbers with an underline below them.

Write numbers with a strikethrough on them.

Write numbers in a superscript font.

Write numbers in a subscript font.

Change digits in a number to Unicode look-alikes.

Change the given numbers a little bit.

Change the digits of the given numbers a little bit.

Calculate the complexity (entropy) of a number.

Test if the given number is numberwang.

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Random Number Generator

Pick a number - how to use the random number generator., possible applications of the random number picker, what is rng, and how do random number generators work, true random number generators and pseudorandom number generators.

This random number generator can produce pseudorandom numbers within a given range. You can pick numbers from -999,999,999,999,999 to 999,999,999,999,999, choose to generate decimals or integers, include or exclude the minimum and maximum values, disallow duplicates (random number generator with no repeats), and sort results from smallest to largest.

It can serve as a single random number picker or a random number list generator . In the text below, you'll find information on how to use this random sequence generator. It will also answer the questions: "what is RNG?", "what is the difference between pseudorandom number generators and true random number generators?" and "how do random number generators work?"

The numbers generated by this lucky number generator are pseudorandom - not truly random, but suitable for most purposes. However, be careful if you want to use it to encrypt top-secret government documents.

Single random number generator

If you want to generate one random number, choose a number that will be the lower limit (the minimum value), and then pick a number that will be the upper limit (the maximum value). To generate again, click the arrow below the "Result" field. (Make sure the "autosave" option is turned on by clicking the floppy disk icon next to the "Minimum value" and "Maximum value" fields).

By default, minimum and maximum values are included in the range of numbers generated. If you want to exclude them, click "advanced mode" (below the "Result" field), and you'll see the option to exclude one or both.

You can also generate decimals (up to two decimal places) - to do that change the "type of number(s)" setting.

Random number list generator

If you choose the "multiple numbers" option in the "Generate" field, input how many numbers you need, and you'll see a sequence of random numbers.

In the advanced mode, you can also choose whether you want to allow duplicates in the random list and whether you want the results to be sorted (from smallest to largest).

If you want to generate numbers with the same settings again, click the "autosave" option to the right of the variables you want to stay the same.

Here are some ways you can use the random number generator. It may be helpful if you need the following:

a random number list generator (random number table generator)

Choose the "multiple numbers" option and input how many numbers you need (the list's length).

a phone number generator

Choose the "multiple numbers," enter "7" into the "how many" field (or another adequate number if you're not in the USA), and set the minimum value to 0 and the maximum value to 9. If 0 is the first number of the sequence, try again. The sequence will be a random phone number.

a random 4-digit number generator

Set the minimum value to 1,000 and the maximum value to 9,999.

a random number sequence generator

Works the same as a random list generator; see above.

a random number generator no repeats

If you generate multiple numbers and want no repeats, go to advanced mode and set "no" in the "allow duplicates" section.

to pick a random number between 69 and 666

Set the minimum value to 69 and the maximum value to 666. RNGesus will forgive you. 😈

to choose a random number between 1 and 4

Set the minimum value to 1 and the maximum value to 4.

to generate 5 random numbers

Choose "multiple numbers" in the first field and enter "5" in the "how many" field.

to pick a number from 1 to 10

Set the minimum value to 1 and the maximum value to 10.

RNG (random number generator) is a device that produces a sequence of numbers that can't be predicted (each outcome has the same probability of being chosen).

Rolling dice is a random hardware number-generating method (and our dice probability calculator is its analog version). Each result has the same chance of appearing ( P = 1/6 ). The same goes for flipping a coin - in our coin flip probability calculator , you can calculate the probability of getting heads and figure it's equal to 50%, and so is the probability of getting tails (not including the possibility of it landing on its side). If you're curious enough, you can try flipping a coin 100 times to check that the longer you flip, the closer you get to an even distribution of outcomes. This phenomenon is known as the law of large numbers.

Although rolling dice is fun, using a software is much quicker and more convenient. But how can computers produce random results if they're entirely deterministic? All that computers do is follow instructions, so how can anything they do be random?

One solution is relying on some external input, which is truly random. For example, computers can use data from a piece of hardware that measures a random physical phenomenon like background radiation. These types of devices are called true random number generators.

Another way is to produce an outcome that seems unpredictable but, in fact, is the result of a strictly defined mathematical process. Software that does this is called a pseudorandom number generator . It takes in a "random enough" number (a seed), e.g., a part of the current time in the system's clock, and performs a function on it. The result is a pseudorandom number.

For many purposes (like gameplay or graphics), pseudorandom generators are enough, but true random number generators are needed especially for encryption.

This number generator is pseudorandom and uses the JavaScript function Math.random(). The algorithm which produces the result depends on the web browser you use. Nowadays, most browsers use the xorshift128+ algorithm, which is based on bitwise operations, which are manipulation of data at the level (learn what a bit is in our byte conversion tool)

What does RNG mean?

RNG stands for random number generator. It is an algorithm that produces a sequence of numbers that can't be predicted, so each outcome has the same probability of being chosen.

We distinguish between true random number generators (TRNG) and pseudorandom number generators (PRGN). PRNG are often used in computer games while TRNG are used for encryption.

How do random number generators work?

There are two main principles to generate random numbers:

  • True random number generator algorithms take the current value of a physical environmental attribute that is constantly changing in a way that is practically impossible to model.
  • Pseudorandom number generator algorithms reproduce numbers by taking a seed as an input and performing a precisely defined algorithm on it.

What is a pseudorandom number?

A pseudorandom number is an outcome that seems unpredictable but, in fact, is the result of a strictly defined mathematical process. The algorithms of pseudorandom number generators (PRGN) take a seed to create random numbers. They are used widely in simulations, computer programming, and as long as the seed stays a secret, also in cryptography.

How to generate a new phone number?

To generate a new phone number:

  • In the random number generator, choose the adequate number of digits for a phone number of your desired country (7 digits for USA).
  • Set the minimum value to 0 and the maximum value to 9.
  • If 0 is the first number of the sequence, let the generator run again.
  • The resulting sequence will be a random phone number.

How to generate a random number in Python?

There are many ways to generate a pseudorandom number or sequence in Python. Here are some useful ones:

  • random.randint(a, b) generates random integers;
  • random.random(a, b) generates floating point numbers; and
  • random.sample(a, b, length_of_list) generates sequences of random numbers.

Consult Python's documentation for more functions in the random module.

Beware: Python uses the Mersenne Twister algorithm as its default PRNG. It is completely unsuitable for cryptographic purposes because its seeds are predictable.

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Random Numbers:

Random number generator.

Its the core of all randomness. Pick a number or generate a whole sequence of numbers within a minimum and maximum value (inclusive) while including or suppress duplicates. Your device is used to quickly generate these numbers, completely random and unique to you every time.

Change the quantity to one if you just want it to pick a number.

You can switch the presentation to roll some dice instead. Or change gears completely with the phone number generator or random letter generator .

Useful Generators

5 Digit Random Number Generator

This random number generator generates a 5-digit random number. The user can trigger the generation of a new number by clicking on the ‘Generate Number’ button. The generated number is displayed on the screen for the user to view. The generated number will be a random number between 10000 and 99999, ensuring that it is always 5 digits long. This generator is useful for any situation that requires a random 5-digit number, such as generating unique codes or passwords.

Random Number Generator

Click the button to generate a 5-digit random number:

How To Use The 5 Digit Random Number Generator

  • Click the “Generate Number” button to generate a new random number.
  • Wait for the generator to finish generating the number.
  • The 5-digit number will displayed below the button in red.
  • Use the generated number as needed, such as for creating unique codes or passwords.
  • If you need another number, click the “Generate” button again to generate a new one.

That’s it! Using this generator should be quick and easy, allowing you to generate random 5-digit numbers whenever you need them.

List Randomizer

Feed the randomizer any number of items (numbers, letters, words, IDs, names, emails, etc.) and it will return them in a truly random order, resulting in a randomly shuffled list. Free online random list generator & list shuffler.

Related randomizers

  • Using the randomizer
  • How many items can the randomizer process?
  • Example applications of the randomizer

Random Team Picker

Random awards picker, randomly distributing chores or tasks, shuffling song lists.

  • Is the randomized list truly random?
  • Shuffling algorithm used in the randomizer
  • Randomizer vs. Randomiser

    Using the randomizer

Using this list randomizer you can shuffle any list in random order. It uses strong cryptographic algorithms to generate random numbers which are then used in an algorithm for unbiased randomization of the list items (more on this below). The result is a truly randomly shuffled list consisting of the initial items.

To use the tool, simply enter a list of items of any sort, one item per row (copy/pasting from a spreadsheet works great). It could be a list of numbers, words, names, emails, countries, songs, tasks, and so on. This website uses a secure connection over HTTPS and does not store any of the information you enter in the field above, so the randomizer should generally be safe to use even for somewhat sensitive information, but it is best that you consult your information security officer if you have any concerns.

The easiest way to retrieve the randomized list is to select it all (Ctrl+A on a PC), and then copy it (Ctrl+C on a PC).

    How many items can the randomizer process?

The maximum number of items per list the randomizer will process is 100,000 . If your items contain a lot of text this number may be subject to further restrictions such as the maximum request size allowed, or the memory limit allotted to our scripts. If you run into such issues, consider replacing the items with short numerical item IDs before feeding them to the shuffler as a list.

    Example applications of the randomizer

A free online randomizer like this can have many possible uses. Here we list a few more common ones.

The classic way to randomly distribute players across teams in a sports game or board game is to randomly draw names out of a hat. Using the list randomizer you can spread players into two or more teams fairly and without bias. Simply enter all the player names and click "Randomize list". If you need two teams, select the first half of the shuffled names for team 1 and the second for team 2. A similar process can be followed for any number of teams as long as the total number of players is divisible by the number of teams to fill. The same logic can be used to distribute students for school group projects.

Despite the above examples, it is more convenient to use our dedicated random team generator which supports multiple teams easily.

If you have a number of names, emails, or identifiers of some sort, and you want to randomly sort them so that only the top 1, 5, 10 etc. receive an award, you can enter the list and randomize it to obtain the list of winners. If the awards are numbered from, say, 1 to 10, you can dole out the awards following the order of the shuffled list.

In case you need to distribute chores or tasks over a group of people or over several days simply list the chores or tasks and shuffle them with our software. Then start with the first on the list and proceed till the end. Similarly, you can randomize a list of your child's names to determine in what order they will do the dishes, sweep the floors, or throw out the garbage in the next few days.

If you are a schoolteacher, you may use this to randomly pick students for different home assignments, projects, etc. While a physical spinning wheel might be more fun, using an online list randomizer is easier.

In yet another scenario, you might want to shuffle a list of songs, books, games, or other things you want to get in random order. In this sense our tool can be used as a random order generator.

These are just several scenarios for using a list shuffler, but we are sure you can come up with many more.

    Is the randomized list truly random?

If your requirements for the randomness of the shuffle are high, you may be wondering if you can trust that our randomizer engine results in unbiased shuffles . Bias here has the technical meaning of 'systematically skewed'. In list shuffling a systematic skewness will be exhibited if items in a certain position in the initial list have an expected probability for ending up in a given position in the shuffled list which is different than the probability of ending up in any other position.

In order to check the randomizer unbiasedness , we devised a straightforward simulation , consisting of shuffling a list of 4 items 4,000,000 times. For simplicity, the four items were the numbers 1, 2, 3, and 4, fed to the randomizer each time in that order.

The results were collected and for each of the four possible positions we summed up the numbers that ended up there in the 4,000,000 simulations. This is the resulting histogram:

randomizer list shuffle simulation

As you can see, there is no bias towards any of the positions, each having a sum of approximately 1,000,000 out of the total sum of 4 million. A statistical goodness-of-fit test was conducted which resulted in a p-value of 0.86, firmly indicating conformity to the expected uniform distribution. As a further precaution we examined the distributions of ones, twos, threes and fours in all positions and found them to be uniformly distributed across them. Goodness-of-fit tests were performed for each of these and the results were again within the expected bounds, confirming that our randomizer produces truly random shuffled lists which should be safe to use in any application requiring robust randomness in the shuffle.

    Shuffling algorithm used in the randomizer

For this random list generator we employ the robust, efficient, and unbiased Fisher–Yates shuffle [1] , also known as the Knuth shuffle . In particular, we implement its modern variant (the initial algorithm was for pen, paper, and a dice!) as described in Richard Durstenfeld's 1964 work [2] . The algorithm was popularized by D.Knuth in his book "The Art of Computer Programming".

The random numbers required for the algorithm's application are generated using a cryptographic pseudo-random number generator (CPRNG) supplied by urandom, the Linux kernel's random number source.

    Randomizer vs. Randomiser

A brief note for those of you who might be confused and wondering as to the correct spelling of the word. Both are correct, however. 'Randomizer' is the American version while 'Randomiser' is the preferred spelling in British English.

    References

1 Fisher, R.A., Yates, F. (1948) [1938] "Statistical tables for biological, agricultural and medical research" (3rd ed.), London: Oliver & Boyd pp.26–27.

2 Durstenfeld, R. (1964) "Algorithm 235: Random permutation", Communications of the ACM 7(7),p.420. DOI:10.1145/364520.364540

3 Knuth, D. E. (1969). "Seminumerical algorithms. The Art of Computer Programming." 2, Reading, MA: Addison–Wesley pp. 139–140.

Cite this randomizer & page

If you'd like to cite this online randomizer resource and information as provided on the page, you can use the following citation: Georgiev G.Z., "List Randomizer" , [online] Available at: https://www.gigacalculator.com/randomizers/randomizer.php URL [Accessed Date: 23 Feb, 2024].

     Random generators

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Generate Random Numbers in Python

  • March 2, 2022 March 22, 2023

Generate random numbers in Python Cover Image

In this tutorial, you’ll learn how to generate random numbers in Python . Being able to generate random numbers in different ways can be an incredibly useful tool in many different domains. Python makes it very easy to generate random numbers in many different ways.

In order to do this, you’ll learn about the random and numpy modules, including the randrange, randint, random, and seed functions. You’ll also learn about the uniform and normal functions in order to create more controlled random values.

By the end of this tutorial, you’ll have learned:

  • How to generate random floating point values and integers
  • How to generate random numbers between different values
  • How to create lists of random numbers
  • How to generate a random number following a gaussian distribution

Table of Contents

Generate Random Floating Point Value in Python

Python comes with a package, random , built in. This means that you don’t need to install any additional libraries. The library makes it incredibly easy to generate random numbers. Let’s first see how to create a random floating point between 0 and 1 .

Let’s break down what we did here:

  • We imported the random library
  • We used the .random() function from the library

The random() function is used to generate a random float between 0 and 1.

Generate a Random Float Between 2 Numbers

While the random() function generates a random float between 0 and 1. However, there may be times you want to generate a random float between any two values. For this, you can use the .uniform() function . Let’s see how this works:

You can see that the random number that’s returned is between (and can include) the boundary numbers.

In the next section, you’ll learn how to generate a random integer in Python.

Generate Random Integer in Python

The random library makes it equally easy to generate random integer values in Python. For this, you can use the randint() function, which accepts two parameters:

  • a= is the low end of the range, which can be selected
  • b= is the high end of the range, which can also be selected

Let’s see how we can generate a random integer in Python:

Generate Random Numbers Between Two Values in Python

In the example above, we used 0 as the starting point. However, if we wanted to generate a random number between two values, we can simply specify a different value as the starting point (including negative values).

Let’s repeat this example by picking a random integer between -100 and 100:

Generate Random Numbers Between Two Values at Particular Steps in Python

In this section, you’ll learn how to generate random numbers between two values that increase at particular steps. This means that say you wanted to choose a random number between, say, 0 and 100, but only in multiples of 3.

For this, you can use the randrange() function. Let’s see how this works:

The important piece to note here is that the upper limit number is not included in the selection. In order to include it, simply add 1 to the value, such as random.randrange(0, 101, 3) .

Generate a List of Random Numbers in Python

In this section, you’ll learn how to generate a list of random numbers in Python. Because this can be done in different ways, we’ll split this section into multiple parts. By the end of this, you’ll learn how to select a list of random floats, random integers, and random integers without repetition.

Generate a List of Random Floats

In order to generate a list of random floats, we can simply call the .random() or .uniform() functions multiple times. We can use either a for loop or a list comprehension.

In the examples below, we’ll use a Python list comprehension to generate two lists: one with random floats between 0 and 1 and the other with random floats between two specified numbers:

  • We instantiated a new list, random_list which holds a list comprehension
  • The list comprehension repeats calling the .random() function 4 times.

We can apply the same approach to create a list of random floats between two given numbers:

Generate a List of Random Integers

We can apply the same approach to generate a list of random integers. To do this, we’ll create a list comprehension that calls the random.randint() function multiple times. Let’s see how we can create a list of 5 random integers between 50 and 100:

Generate a List of Random Integers without Substitution

In this section, you’ll learn how to generate a list of random integers without substitution. This means that you can select a number once, and only once. In order to do this, you can use the random.sample() function.

The function expects a list of values and the number of values to select. So, say you wanted to select five values without substitution between 0 and 15, you could write:

Generate a Random (Normal) Gaussian Distribution in Python

The random library also allows you to select a random value that follows a normal Gaussian distribution. In order to do this, you can use the gauss() function, which accepts both the mean and the standard deviation of the distribution .

Let’s see how you can generate a random value from a distribution with the mean of 10 and a standard deviation of 1:

Want to create an entire distribution? Check out this article here, which teaches you how to produce an entire Gaussian (Normal) distribution using Numpy .

The random library also comes with helpful ways to generate random numbers from other types of distributions. Check out the full list below:

  • Beta distribution:  random.betavariate()
  • Exponential distribution:  random.expovariate()
  • Gamma distribution:  random.gammavariate()
  • Gaussian distribution:  random.gauss()
  • Log normal distribution:  random.lognormvariate()
  • Normal distribution:  random.normalvariate()

Create Reproducible Random Numbers in Python

There will be many times when you want to generate a random number, but also want to be able to reproduce your result. This is where the random.seed() function come in. This allows you to set a seed that you can reproduce at any time.

Let’s see how we can do this:

Let’s break this down a little bit:

  • We imported the library
  • We then instantiated a random seed, using the value of 100
  • Then when we printed a random float, a value was returned
  • If we were to run this again, the same value would be returned

In this tutorial, you learned how to generate random numbers using Python. You learned how the random library works to generate random numbers, including floats and integers. You also learned how to generate random numbers from different ranges of numbers, including only multiples of numbers.

You then learned how to generate lists of random numbers, including floats and integers, as well as without substitution. Finally, you learned how to select random numbers from a normal distribution and how to reproduce your results.

Additional Resources

To learn more about related topics, check out the tutorials below:

  • Python: Select Random Element from a List
  • Python: Shuffle a List (Randomize Python List Elements)
  • NumPy for Data Science in Python
  • Python Random: Official Documentation

Nik Piepenbreier

Nik is the author of datagy.io and has over a decade of experience working with data analytics, data science, and Python. He specializes in teaching developers how to use Python for data science using hands-on tutorials. View Author posts

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Random 5 Digit Number Generator

Generate a list of 5 digit random numbers with this random number generator . No sign up needed to use this app. Simply click on the generate button to get a list of random 5 digit numbers.

Generate Random 5 Digit Numbers

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Random 5 Digit Number Generator

5 digit number generator online tool allows you to randomly generate a list of five digit numbers..

randomly generate 5 numbers

5 Ways to Generate Random Numbers in Excel

Not every user will have a need for random numbers in Excel. Most people work with fixed numbers and formulas and may have no need for random numbers to appear in their reports.

However, a random number generator does have a huge use when working with different scenarios on a set of data or when performing various statistical analyses.

A financial model may use a stochastic simulation that is dependent on probabilities. The model may need to be run thousands of times, but with the random number generator providing the parameters of each simulation.

Whatever your need for random numbers, Excel has several ways to generate them.

In this post, I’ll show you all the methods you can use to insert random numbers into your workbooks.

Generate Random Numbers with the RAND function

The first way I will show you is the easiest way to generate random values in Excel.

There is a very simple RAND function that requires no parameters and will generate a random number between 0 and 1.

Syntax for the RAND Function

randomly generate 5 numbers

This function has no required or optional arguments. The function is always entered with an empty set of parenthesis.

This function will generate a decimal random number between 0 and 1, but not including 0 or 1.

Repeated values are possible but unlikely since the RAND function produces numbers from a continuous range of numbers.

The values that are returned will follow a uniform distribution. This means that any number between 0 and 1 is equally likely to be returned.

Generate Random Numbers Between Any Two Numbers

A decimal number between 0 and 1 may not be too useful if you need numbers between 1 and 10.

But you can use a simple formula involving the RAND function to generate random numbers between any two numbers.

In general, you can create a random number between X and Y by using the above formula.

randomly generate 5 numbers

For example, to generate numbers between 1 and 10 you can use the above formula.

This multiplies the random number generated by 9 and then adds 1 to it. This will produce decimal numbers between 1 and 10.

Generate Random Integer Numbers Between Any Two Numbers

Another possible need you may encounter is to generate random whole numbers between two given numbers. This can also be done using a simple formula.

In general, you can use the above formula to generate random integer numbers between two values X and Y.

randomly generate 5 numbers

For example, the above formula will create random integer numbers between 1 and 10.

This is the same formula as before, but using the ROUND function to round to zero decimal places.

You can copy this formula down the column on the spreadsheet, and if you keep pressing F9 to re-calculate, you will see various combinations of numbers from 1 to 10.

Since the set of possible numbers is discrete, the random numbers generated may well be duplicated in the list, depending on what the minimum and maximum are of the range.

randomly generate 5 numbers

This also works for producing negative numbers. Suppose you need to generate random integer numbers between -3 and 4, then the above formula will be what you need.

Multiplying the RAND function by 7 will produce random numbers between 0 and 7. Add -3 to the result and round to zero decimal places, and this will give the range of random numbers of -3 to 4.

Generate Random Numbers using the RANDBETWEEN Function

Excel has a useful function for generating random numbers within a range of an upper and lower number.

This is easier to use than using the RAND function as it includes extra operators to arrive at your specific range.

Syntax for the RANDBETWEEN Function

  • bottom is the lower range for the values to return.
  • top is the upper range for the values to return.

Both of these arguments are required.

This function will produce random integer numbers between the bottom and top values. This function will also return the upper and lower limits as possible values as it’s not strictly between in this function.

Example with the RANDBETWEEN Function

randomly generate 5 numbers

For example, if you wanted random numbers between -3 and 4, as in the previous example, you can use the above formula.

Note that the RANDBETWEEN function can only produce integer numbers. There is no way of making the function produce decimal numbers. However, it is considerably less complicated than using the RAND function with operators to achieve the same result.

Generate Random Numbers with the RANDARRAY Function

Usually, it’s the case that you don’t want just a single random value but an entire set of random values.

The RANDARRAY function is the perfect solution for this.

It will populate a range of cells with an array of random numbers, which can be very powerful.

This function is only available on the Microsoft 365 version of Excel.

Syntax for the RANDARRAY Function

  • Rows is the number of rows to return.
  • Columns  is the number of columns to return.
  • Min  is the minimum value for the random numbers.
  • Max is the maximum value for the random numbers.
  • Whole_Number is TRUE to return whole numbers, and FALSE to return decimal numbers.

All the arguments are optional for this function.

If no parameters are included, you will get a single random number with decimal places, in the same way as the RAND function.

Example with the RANDARRAY Function

randomly generate 5 numbers

To generate an array of 4 rows and 3 columns of whole random numbers between 6 and 14 you can use the above formula.

This will produce an array of values. Notice the blue border around the numbers? These are all produced from a single formula!

Note that the top left-hand corner of the array is always anchored on the cell that the formula is in. Pressing F9 to recalculate the spreadsheet will change all the numbers in the array.

If you do not put a minimum or maximum value, the default of 0 to 1 will be used.

The minimum value must be less than the maximum value otherwise there will be a #VALUE! error.

The array will automatically resize if you change either the rows or columns parameters in the RANDARRAY formula. This is why they’re known as dynamic arrays.

Warning : If there is already data in one of the cells in the output range that you have entered, you will get a #SPILL! error.  No data will be overwritten.

Generate Random Numbers with the Analysis Tools Add-In

There is another method that can be used to insert random numbers without using a formula.

You can use an add-in to create random numbers. Excel comes with an Analysis Tool Pak add-in, but you will need to install it before you can use it.

Install the Analysis Toolpak

randomly generate 5 numbers

Here are the steps to install the Analysis Tool Pak add-in.

  • Click on the File tab in the ribbon.

randomly generate 5 numbers

  • In the lower left-hand pane of the window, scroll down and click on Options . You can also use the keyboard shortcut Alt , F , T from the spreadsheet window to open the Options window.

randomly generate 5 numbers

  • In the left-hand pane of the pop-up window, click on Add-Ins.
  • At the bottom of the main window displayed, select Excel Add-ins from the dropdown and click on the Go button.

randomly generate 5 numbers

  • This will display a pop-up window containing all available add-ins for Excel. Check the box for Analysis ToolPak and then click OK .

randomly generate 5 numbers

  • On the Excel ribbon, on the Data tab, there is now an extra group called Analysis with one button called Data Analysis .

Generate Random Numbers with the Analysis Toolpak

randomly generate 5 numbers

Click on the Data Analysis button in the Analysis group.

This will display a pop-up window. Scroll down and select the Random Number Generation option and then click OK .

randomly generate 5 numbers

A new pop-up window will appear where you can enter your parameters to generate the random numbers.

There are several settings that can be customized.

  • Number of Variables This is the number of columns of random numbers that you want in your output table. If left blank, then all columns will be filled in the output range that you specify.
  • Number of Random Numbers This is the number of rows of random numbers that you want to generate. If left blank, the output range that you specify will be filled.
  • Distribution  You can select several distribution methods from the drop-down such as uniform or normal distribution. Different options will become available in the Parameters section depending on your selection here.
  • Parameters  Enter the values to characterize the distribution selected.
  • Random Seed This is optional and will be the starting point for the algorithm to produce the random numbers. If you use the same seed again, it will produce the same random numbers. If left blank, it will take the seed value from the timer event.
  • Output Range Enter the upper left cell of where the table is to be constructed in the spreadsheet. If you have left the Variables parameter blank, then you will need to specify an entire range. Note that existing data in that range will be overwritten.
  • New Worksheet Ply This option will insert a new worksheet within the workbook and will paste the results at Cell A1. Enter a sheet name in the adjacent box, otherwise, a default name will be used.
  • New Workbook This will create a new workbook and paste the results into cell A1 in the first sheet.

randomly generate 5 numbers

Press the OK button and Excel will insert the random number according to the selected options.

Notice that unlike the formula methods previously shown, these numbers are hardcoded and will not change when you refresh calculations in the workbook.

Generate Random Numbers with VBA

VBA (Visual Basic for Applications) is the programming language that sits behind the front end of Excel, and this can also be used to generate random numbers.

However, it is more complicated than simply entering a formula into a cell in Excel, and you do need some programming knowledge to use it.

randomly generate 5 numbers

To open the VBA editor, use the Alt + F11 keyboard shortcut.

In the left-hand pane of the window (Project Explorer), you will see the workbooks that are open (including add-ins) and the sheets available.

On the menu at the top of the window, click on Insert and then click on Module . This will add a module window to the current spreadsheet. Paste or add the following code to the module.

randomly generate 5 numbers

Press F5 to run this, and a message pop-up will appear in Excel with a random number displayed. Press OK and you will return to the code window.

Run the code again and a different random number will be displayed. The random number will be between 0 and 1, but will not include the values of 0 or 1.

You can also give the Rnd function a parameter, which is a seed for the starting point of the algorithm to produce the random numbers.

If the seed value is set to a negative number or zero, then the same random number will be displayed each time.

Using VBA functions, you can emulate all the functionality of the front-end methods that have been covered in this article.

For example, if you wanted to generate whole random numbers between 3 and 10, then you would use the following above code.

This code multiplies the random number, by 7, and then adds 3 to it, and then rounds to zero decimal places.

Suppose that you then wanted to display your random numbers in the grid. You can do this with the following code.

randomly generate 5 numbers

This code uses a For Next loop to iterate 5 times through the random number calculation and enter the results in a column of cells starting at cell A1.

Remember that any data already there will be overwritten, and there is no warning or undo feature available. Save any previous work beforehand!

There is also a VBA function called Randomize . You can use this before the Rnd function to reset the seed value to the timer event, or to any parameter given.

Generate Random Numbers without Duplicates or Repeats

You may well have a situation where you want to generate a range of random numbers, but you do not want to see any duplicate values appearing.

You may want to select 3 random numbers between the numbers from 1 to 10, but where each of the 3 selected numbers is unique.

You could generate random numbers with the RANDBETWEEN function and then use the Excel function Remove Duplicates from the ribbon, but this still may not give you all the numbers required.

There are several possible solutions available.

Solution with RANK.EQ and COUNTIF Functions

If you don’t have access to the RANDARRAY function in Excel, then you can use a combination of RANK.EQ and COUNTIF to get unique random numbers.

You can create your random numbers using RANDBETWEEN and then use a formula in the next column to rank them thereby giving you a randomly sorted sequence from 1 to 10.

randomly generate 5 numbers

In cell B2, enter the above formula . Copy this formula down so that there are 10 rows of random numbers going down to cell B11.

You will notice that some numbers may be duplicated and some are not shown at all.

You can then use the RANK.EQ function to rank them so as to create a sequence from 1 to 10 but that is sorted randomly.

randomly generate 5 numbers

In cell C2, enter the above formula.

Note that there are absolute references used (the $ signs) so that formula references stay fixed as you copy the formula down.

Copy this formula down to cell C11, and this will display all the numbers between 1 and 10, but in random order.

To explain this formula in more depth, it uses two functions RANK.EQ and COUNTIF .

  • Number is the number that we want to find the rank of in the array.
  • Ref is the array where we want to search for the number.
  • Order is optional and allows you to find the rank in either ascending or descending order. If its omitted then ascending order is used.

The RANK.EQ function returns the rank of a number within an array of numbers.

  • Range is the range that is being searched for instances of the criteria.
  • Criteria is the value to match within the range.

The COUNTIF function counts the number of cells based on a given criterion. In this case, it is counting how many times a given random number has appeared in the list.

For each random number the RANK.EQ function will determine its ranking position relative to the other random numbers. But if the random numbers contain duplicates, then they will create a tied ranking.

The COUNTIF function will compensate for any ties in the ranking and will add one to the rank for each time the random number has previously appeared.

This creates a unique ranking where ties don’t get the same rank.

Since this rank is based on a set of random numbers the result is the same as randomizing a list of numbers from 1 to 10.

Now, if you only want 5 non-repeating numbers, you only need to take the first 5 from the ranking list.

Solution with VBA

You could also use VBA to generate a string of random numbers from 1 to 10 without duplicates.

This code iterates through values from 1 to 5, generating a random number between 1 and 10 each time.

It tests the random number to check if it has already been generated. This is done by concatenating successful numbers into a string and then searching that string to see if the number has already been used.

If it has been found, then it uses the label Repeat to go back and re-generate a new number. This is again tested that it has not already been used. If it is a new number, then it is added to the sheet.

Solution with Dynamic Arrays

If you have dynamic arrays in Excel, then there is a single formula method to avoid repeating values.

Suppose you want to return 5 numbers from the sequence 1 to 10. You want each number selected to be unique.

This can be done using a combination of the SEQUENCE , SORTBY , RANDARRAY , and INDEX functions.

randomly generate 5 numbers

The above formula creates a sequence of numbers from 1 to 10.

It then sorts them in a random order using the SORTBY function and sorting on a column of random numbers generated by the RANDARRAY function. The effect is to sort the sequence in random order.

Now if you want to get 5 random and unique numbers you only need to take the first 5 numbers from the randomly sorted sequence.

This is exactly what the INDEX function does! This part of the formula will return the first 5 numbers from the randomly sorted sequence.

There are several ways to generate random numbers in Excel.

Whether you need whole numbers, decimals, or a range of random numbers with an upper and lower limit, the facility is available. Excel is extremely versatile on this topic.

However, bear in mind that these numbers are pseudo-random numbers generated by an algorithm.

Although the random number generator passes all the tests of randomness, they are not true random numbers.

To be a truly random number, it would have to be driven by a random event happening outside the computer environment.

For most purposes of constructing general simulations and statistical analysis, the Excel random number generator is considered fit for the purpose.

Have you used any of these methods for generating random numbers in Excel? Do you know any other methods? Let me know in the comments below!

About the Author

John MacDougall

John MacDougall

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randomly generate 5 numbers

I’m John , and my goal is to help you Excel!

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randomly generate 5 numbers

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Fantasy 5 Number Generator

Use the Fantasy 5 Number Generators below if you’re looking for a set of numbers to enter into the next draw. All you need to do is hit the ‘Generate’ button and a random set will appear straight away.

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Random 5 Digit Numbers

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C Random Number Generator

This technique has an intriguing world of RNGs and techniques to boost your programming experience, so keep reading the following chapters for more.

JUMP TO TOPIC

1. Include Necessary Headers

2. use a random engine, 3. seed the engine, 4. determine the distribution, 5. generate random number, how to initiate random integers within a specific range in c++, how to optimize c++ random number generator for performance, how to generate random floats and doubles in c++, how to compare different random number generators in c++, how to create a c++ random number generator.

You can create a C++ random number generator by including the necessary headers and selecting an engine, like std::default_random_engine or std::mt19937. After setting it up, you determine the desired distribution, such as std::uniform_int_distribution, to specify number ranges.

You must set the stage before you can begin working on any coding project. When generating random numbers in C++, you must first include the necessary headers. If you’re trying to fix a leaky faucet, you wouldn’t grab a hammer; you’d need a wrench. Similarly, to generate random numbers in C++, you require specific tools or, in this case, headers.

Necessary Headers in C++

To kick things off, you’ll need to use the #include directive, a command that tells your C++ program to grab a particular tool. For our random number generator , the required headers are:

#include <iostream>

#include <random>

The <iostream> header allows your program to interact with the user by displaying output or getting input. As the name suggests, the <random> header provides the tools necessary for generating random numbers.

Now, you need to understand and use something called a random engine. Picture it like a magical box. You give this box a little nudge, and out pops a number. In C++, this box is known as a random engine.

For most purposes, the std::default_random_engine is a good choice. To use it, you’ll first declare and then initialize it:

std::default_random_engine generator;

However, if you want your random number generator to produce different sequences of numbers every time you run your program, you should seed it. A popular method to seed is by using the current time:

std::default_random_engine generator(time(0));

Now, every software engineer knows the importance of data structures and their role. In this context, you might wonder, “How does it fit in?” Once you set up your random engine, you’ll use data structures known as distributions to specify the range and type of numbers you want to generate.

For instance, to generate values between 1 and 100, you’d use:

std::uniform_int_distribution<int> distribution(1, 100);

int random_number = distribution(generator);

Now, onto the next big step: seeding your engine. Why is this important? Without getting too technical, seeding ensures you’re not just getting the same sequence of “random” numbers every time you run your program.

Seeding C++ Engine

For this, C++ offers the SRand C++ function. However, most programmers prefer using the more modern tools available in the standard library . One common method is to use the current time as a seed because the time is always changing:

Just remember: once you seed your generator, it’s set. You only need to do it once, right at the start of your program or whenever you want to reset the sequence of random numbers.

With your engine revved and ready, it’s time to decide how you want your numbers. Do you want them all equally likely, like drawing numbers out of a hat? Or do you have more specific requirements? This decision is where the magic of distribution comes in.

The standard library in C++ offers a variety of distributions to cater to different needs. The most common one, especially for beginners, is the uniform distribution. It ensures that every number within a given range is equally likely to pop up.

Here’s a simple example:

However, you might encounter the Mersenne twister if you want more uniqueness in your random number generation. This engine is known for its long period (meaning a very long time before the sequence of numbers repeats) and high-quality random numbers. To use it:

std::mt19937 generator(time(0));  // That’s the Mersenne twister engine!

int random_number = std::uniform_int_distribution<int>(1,100)(generator);

With the engine seeded and your distribution set, you can generate random numbers to your heart’s content.

After setting up your engine and distribution, the next step is the exciting part. It’s like having all the ingredients for a recipe ready, and now it’s time to cook! You’ll use the engine and distribution you previously set up to generate a random number. Here’s a refresher on the pieces you should have:

Generating Random Number

Your chosen engine (like std::default_random_engine or the Mersenne twister with std::mt19937).

Your distribution defines the range and kind of random numbers you want (like std::uniform_int_distribution<int> for integers).

Now, let’s get those numbers:

In this line, you’re asking the distribution to give you a number. It does this by taking a “spin” from the generator (your engine) and converting that spin into a number that fits within the specified range.

You can think of it as a two-step dance. The generator sets the rhythm, and the distribution gives it form.

If you want to generate multiple numbers, just repeat the process in a loop:

for(int i = 0; i < 10; i++) {

std::cout << random_number << std::endl;

With this loop, you’ll print ten random numbers to the screen. Each time through the loop, you ask for a new number from the distribution, which takes another spin from the generator.

To initiate random integers within a specific range in C++, use the std::uniform_int_distribution<int> distribution. Define the desired range by setting its minimum and maximum values. Combined with an engine, this distribution produces random numbers within the specified bounds.

The first step is choosing an engine. C++ offers several, but for this purpose, use the default engine:

Now that the engine is ready, you must decide the range of integers you want. For this, C++ offers a uniform integer distribution. It ensures every integer within our specified range has an equal chance of being chosen.

Let’s say we want numbers between 1 and 100. Here’s how you can set it up:

Getting our Random Integers

With everything in place, generating a random integer is as simple as:

int random_integer = distribution(generator);

You now have a random integer between 1 and 100.

You can optimize C++ random number generators for performance and speed by selecting efficient engines like std::mt19937. It’s crucial to seed the engine just once and avoid unnecessary conversions or checks, streamlining the generation process and enhancing speed and productivity.

Optimizing C++ Random Number Generator

Not all engines are created equal. While the std::default_random_engine is a jack-of-all-trades, you might want to go with the std::mt19937 if performance is a priority. It’s speedy, reliable, and a favorite among many programmers:

std::mt19937 fast_generator;

Constantly re-seeding the generator isn’t just unnecessary and can slow things down. It’s like restarting your car at every stop sign. Seed once at the start of your program or when you genuinely need a new sequence.

You introduce potential slowdowns every time you convert types or add extra checks. Stick to what’s essential and avoid unnecessary overhead.

In C++, to generate random floats and doubles, utilize std::uniform_real_distribution. By setting the desired range, this distribution pairs with an engine to produce random floating-point numbers with precision. Floating-point numbers, or floats and doubles, have decimal points. Sometimes, you need that precision.

While this guide previously discussed std::uniform_int_distribution for integers, you will use std::uniform_real_distribution for floating-point numbers. It works similarly but is tailored for decimals:

std::uniform_real_distribution<double> double_distribution(0.0, 1.0);

std::uniform_real_distribution<float> float_distribution(0.0f, 1.0f);

These distributions will generate numbers between 0 and 1, but you can adjust the range as needed.

Just like with integers, once you have your distribution set up, generating a random float or double is a breeze:

double random_double = double_distribution(generator);

float random_float = float_distribution(generator);

Remember, the key difference between floats and doubles is precision. Floats are usually 32 bits, offering about 7 decimal digits of precision, while doubles are 64 bits, boasting about 15 decimal digits.

You can compare different C++ random number generators by evaluating their uniformity, speed, and cycle length. It’s essential to choose the right engine based on specific requirements, run uniformity and speed tests, and understand the cycle length to determine quality and efficiency.

Different Random Number Generators in C++

Before judging any RNG, it’s crucial to know what makes one good. Generally, a good RNG has three qualities: it’s uniform (each number has an equal chance of appearing), it’s fast, and it has a long cycle before repeating numbers.

C++ offers several RNGs, with the most popular being:

  • std::default_random_engine: It’s the typical choice, but its behavior might differ based on the compiler.
  • std::mt19937: Known as the Mersenne Twister, it’s famed for speed and a super long cycle.
  • std::ranlux48: This one’s a bit slower but provides high-quality random numbers.

A core test for any RNG is checking its uniformity. RNG should be like a fair dice, giving each number an equal shot. To compare RNGs, generate many numbers and check the distribution. If it’s close to being even, it passes the uniformity test.

To compare the speed of different RNGs, you can run each in a loop, generating numbers and time how long each takes. The faster one might be your go-to if you need many numbers instantly:

#include <chrono>

std::chrono::steady_clock::time_point start = std::chrono::steady_clock::now();

// … [RNG code here] …

std::chrono::steady_clock::time_point end = std::chrono::steady_clock::now();

auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end – start).count();

While waiting for an RNG to repeat is impractical, studying its documentation can give insights. The Mersenne Twister, for instance, has a whopping cycle length of two.

Random number generators in C++ are invaluable tools with diverse applications, from simulations to games. To make the most of these tools, it’s essential to:

  • Choose the right RNG based on the specific requirements of your project.
  • Always test for uniformity to ensure fairness and randomness.
  • Prioritize speed, especially for applications needing vast numbers in a short time.
  • Familiarize yourself with the RNG’s cycle length, aiming for longer cycles to avoid repetition.
  • Tailor your RNG choice to the demands of your task, weighing factors like speed against quality.

The RNG C++ concept is valuable for novice and experienced developers, so stop waiting and check it out now!

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Florida Lottery numbers from Feb. 21 drawings. No Powerball winners, 2 win Fantasy 5

randomly generate 5 numbers

There were two winners in the drawings held Wednesday in the Florida Lottery, excluding Cash Pop.

Games played Wednesday, Feb. 21 included: Powerball , Florida Lotto , Cash4Life , Cash Pop and Fantasy 5.

Here are Wednesday's results:

Powerball results from Wednesday, Feb. 21 drawing

  • Winning numbers: 4-27-33-41-42 Powerball: 14 PowerPlay: 2
  • Estimated jackpot: $348 million
  • Winning tickets: No winning tickets sold
  • Next jackpot draw date: Feb. 24 for estimated jackpot of $376 million

Second tier prize

  • Prize: $1 million
  • Winners: No winning tickets sold
  • Double Play winning numbers: 23-49-51-54-58 Powerball: 11

Powerball is a multi-state, multimillion-dollar-jackpot game offered in 48 Lottery jurisdictions, including Florida. The game's starting jackpot is $20 million. Powerball has nine prize levels with lower-tier prizes ranging from $4 to $1 million and up to $2 million with Power Play and $10 million with Double Play.

Powerball tickets cost $2 per play. Powerball with Power Play tickets cost $3 per play. Powerball with Double Play tickets cost $3 per play. Powerball with Power Play and Double Play tickets cost $4 per play.

Common Powerball numbers: Powerball numbers you need to know: These most commonly drawn numbers could help you win

Florida Lotto winning numbers from Wednesday, Feb. 21 drawing

  • Winning numbers Florida Lotto: 2-7-15-25-35-36
  • Jackpot: Rollover
  • Next jackpot draw date: Feb. 24 for estimated jackpot of $3.75 million
  • Winning numbers Double Play: 5-7-8-17-19-47

With Florida Lotto, every ticket purchased includes a randomly generated "multiplier" number that automatically increases non-jackpot cash prizes by two, three, four, five or 10 times. All Florida Lotto tickets cost $2 per play for the base game.

Double Play is an add-on feature that gives players the chance to win additional prizes up to $250,000 during an additional drawing held immediately following the Florida Lotto drawing, using the same numbers and multiplier on their ticket. Double Play costs $1 more per play.

Cash4Life winning numbers from Wednesday, Feb. 21 drawing

  • Winning numbers: 12-26-29-30-32 Cashball: 1
  • Jackpot, $1,000 a day for life: No winners
  • Jackpot, $1,000 a week for life: No winners
  • Next jackpot draw date: Feb. 22

Cash4Life  is a regional multi-state game that offers two lifetime prizes and great odds. For $2, players try to match five white balls (1-60) and the Cash Ball (1-4) to win the top prize $1,000 a day for life.

If you match only the five white balls you win the second prize of $1,000 a week for life.

What to know about Florida Lottery: Ultimate guide to the Florida Lottery, Powerball and Mega Millions

Earn millions with scratch-off games: Florida Lottery scratch-off games offer prizes in the millions

Fantasy 5 winning numbers for midday drawing Wednesday, Feb. 21

  • Winning numbers for midday drawing: 9-10-13-20-23
  • Jackpot: $27,477.31
  • RaceTrac #2394, 3004 E 53rd Ave., Bradenton
  • Publix, 926 S Military Trail, West Palm Beach

Fantasy 5 is a daily draw game with a top prize of approximately $100,000 if won by a single winner. If there is no top-prize winner, the top prize rolls down to the 4-of-5 and 3-of-5 prize levels. Tickets cost $1 per play.

Fantasy 5 winning numbers for evening drawing Wednesday, Feb. 21

  • Winning numbers evening drawing: 3-8-19-23-29
  • Jackpot: Rolldown

If there is no top prize winner, the money in the top prize pool rolls down and is shared equally among winners who picked four out of the five numbers, with a maximum prize of $555 per winner.

Cash Pop winners from Wednesday, Feb. 21 drawing

  • Morning: 4 winners
  • Matinee: 9 winners
  • Afternoon: 10 winners
  • Evening: 12 winners
  • Late night: 7 winners

Cash Pop gives players a chance to win prizes up to $1,250 by matching just one number. Select a number from 1 to 15 or select up to 15 numbers. Then select the amount you want to play per number: $1, $2, or $5. The dollar amount played determines the cash prize you could win. Lastly, select how many consecutive draws you want to play; you can select up to 10 consecutive draws.

The independent source for health policy research, polling, and news.

KFF Health Tracking Poll February 2024: Voters on Two Key Health Care Issues: Affordability and ACA

Audrey Kearney , Alex Montero , Isabelle Valdes , Ashley Kirzinger , and Liz Hamel Published: Feb 21, 2024

  • Methodology

This KFF Health Tracking Poll was designed and analyzed by public opinion researchers at KFF. The survey was conducted January 30 – February 7, 2024, online and by telephone among a nationally representative sample of 1,309 U.S. adults in English (1,231) and in Spanish (78). The sample includes 1,026 adults ( n= 58 in Spanish) reached through the SSRS Opinion Panel either online (n=1,002) or over the phone (n=24). The SSRS Opinion Panel is a nationally representative probability-based panel where panel members are recruited randomly in one of two ways: (a) Through invitations mailed to respondents randomly sampled from an Address-Based Sample (ABS) provided by Marketing Systems Groups (MSG) through the U.S. Postal Service’s Computerized Delivery Sequence (CDS); (b) from a dual-frame random digit dial (RDD) sample provided by MSG. For the online panel component, invitations were sent to panel members by email followed by up to three reminder emails.

Another 283 ( n= 20 in Spanish) interviews were conducted from a random digit dial telephone sample of prepaid cell phone numbers obtained through MSG. Phone numbers used for the prepaid cell phone component were randomly generated from a cell phone sampling frame with disproportionate stratification aimed at reaching Hispanic and non-Hispanic Black respondents. Stratification was based on incidence of the race/ethnicity groups within each frame.

Respondents in the phone samples received a $15 incentive via a check received by mail, and web respondents received a $5 electronic gift card incentive (some harder-to-reach groups received a $10 electronic gift card). In order to ensure data quality, cases were removed if they failed attention check questions in the online version of the questionnaire, or if they had over 30% item non-response, or had a length less than one quarter of the mean length by mode. Based on this criterion, one case was removed.

The combined cell phone and panel samples were weighted to match the sample’s demographics to the national U.S. adult population based on parameters derived from the Census Bureau’s 2022 Current Population Survey (CPS), 2021 Volunteering and Civic Life Supplement data from the CPS, and the 2023 KFF Benchmarking survey with ABS and prepaid cell phone samples. The demographic variables included in weighting for the general population sample are sex, age, education, race/ethnicity, region, education, civic engagement, internet use, and political party identification by race/ethnicity. The sample of registered voters was weighted separately to match the U.S. registered voter population using the parameters above plus recalled vote in the 2020 presidential election by county quintiles grouped by Trump vote share. Both weights account for differences in the probability of selection for each sample type (prepaid cell phone and panel). This includes adjustment for the sample design and geographic stratification of the cell phone sample, within household probability of selection, and the design of the panel-recruitment procedure.

The margin of sampling error including the design effect for the full sample and registered voters is plus or minus 4 percentage points. Numbers of respondents and margins of sampling error for key subgroups are shown in the table below. For results based on other subgroups, the margin of sampling error may be higher. Sample sizes and margins of sampling error for other subgroups are available by request. Sampling error is only one of many potential sources of error and there may be other unmeasured error in this or any other public opinion poll. KFF public opinion and survey research is a charter member of the Transparency Initiative of the American Association for Public Opinion Research .

  • Affordable Care Act
  • Health Costs
  • Tracking Poll
  • Medicare's Future
  • Pre-Existing Conditions
  • Prescription Drugs
  • TOPLINE & METHODOLOGY

Also of Interest

  • KFF Health Tracking Poll: Economic Views and Experiences of Adults Who Struggle Financially
  • From Drew Altman: Why Affordability Is the Big Tent

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  1. Random Number List Generator

    randomly generate 5 numbers

  2. Generating Random Numbers With Excel's RAND Function

    randomly generate 5 numbers

  3. How to Generate Random Numbers in Excel (3 Different Ways)

    randomly generate 5 numbers

  4. How to Generate Random Numbers in Excel (3 Different Ways)

    randomly generate 5 numbers

  5. [Solved] make a Raptor program that generate 5 random numbers and store

    randomly generate 5 numbers

  6. Create Random Numbers In Excel (Ultimate Guide)

    randomly generate 5 numbers

VIDEO

  1. Rocket counting of numbers

  2. Generate numbers randomly in #excel using =RANDBETWEEN( ). #exceltips #exceltricks

  3. How to generate random numbers

  4. when you randomly edit numbers

  5. Is Numbers' random number generator random?

  6. How to Generate Numbers Randomly in Picturebox

COMMENTS

  1. 5 Random Numbers between 1-50

    1-10 1-100 1-1000 Pick from a List Multiple Lines 3-digit 4-digit 6-digit 8-digit 9-digit Alpha Hex Binary Advertisement Combinatorics Select 5 unique numbers from 1 to 50 Total possible combinations: If order does not matter (e.g. lottery numbers) 2,118,760 (~ 2.1m) If order matters (e.g. pick3 numbers, pin-codes, permutations)

  2. Random Number Generator

    A pseudo-random number generator is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. Computer based random number generators are almost always pseudo-random number generators. Yet, the numbers generated by pseudo-random number generators are not truly random.

  3. Random Number Generator

    A pseudo-random number generator (PRNG) is typically programmed using a randomizing math function to select a "random" number within a set range. These random number generators are pseudo-random because the computer program or algorithm may have unintended selection bias.

  4. Random Number Generator

    Our number randomizer will pick a number from 1 through 10 at random. To generate a random number between 1 and 100, do the same, but with 100 in the second field of the picker. To simulate a dice roll, the range should be 1 to 6 for a standard six-sided dice.

  5. RANDOM.ORG

    FREE services Numbers Integer Generator makes random numbers in configurable intervals Sequence Generator will randomize an integer sequence of your choice Integer Set Generator makes sets of non-repeating integers Gaussian Generator makes random numbers to fit a normal distribution

  6. Random 5 Digit Number Generator

    Press 'Generate': A simple click will unravel a series of unique 5-digit numbers exclusively for you. Our system utilizes advanced algorithms to ensure that each number generated is distinct from the rest. Why Use a Random 5 Digit Number Generator? Secure Codes: Perfect for generating random access codes, verification numbers, or PINs.

  7. Random Number Generator

    This online random number generator allows you to generate random numbers within a specific range. To use the generator, follow these four simple steps: Enter the lower and upper bounds of the number range. Enter the count of numbers to generate. Select the type of numbers you wish to generate. Click the "Generate" button to create an array of ...

  8. Number Generator

    The sequence of random numbers itself is generated using the formula: Xₙ₊₁ = (aXₙ + c) mod m. It is worth noting that this method depends on the choice of parameters. For example, for the following set: X₀ = 3, a = 4, c = 5, m = 6. we get a short repetitive sequence of. 3, 5, 1, 3, 5, 1. which does not look random.

  9. Generate Random Numbers

    random number generator. world's simplest number tool. Quickly generate a list of random numbers in your browser. To get your list, just specify the minimum and maximum values, and how many numbers you need in the options below, and this utility will generate that many random numbers. Created by developers from team Browserling.

  10. Random Number Generator

    If you want to generate one random number, choose a number that will be the lower limit (the minimum value), and then pick a number that will be the upper limit (the maximum value). To generate again, click the arrow below the "Result" field.

  11. Random Number Generator / Picker

    How To Use Random Number Generator? To choose a random number within a designated span, use a random number generator with two inputs corresponding to the lower and upper range limits. For instance: Selecting multiple numbers: For example, to obtain 10 random numbers ranging from 10 to 50, input these values into the respective fields.

  12. Random Numbers

    Random Number Generator. Its the core of all randomness. Pick a number or generate a whole sequence of numbers within a minimum and maximum value (inclusive) while including or suppress duplicates. Your device is used to quickly generate these numbers, completely random and unique to you every time. Change the quantity to one if you just want ...

  13. 5 Digit Random Number Generator

    This random number generator generates a 5-digit random number. The user can trigger the generation of a new number by clicking on the 'Generate Number' button. The generated number is displayed on the screen for the user to view. The generated number will be a random number between 10000 and 99999, ensuring that it is always 5 digits long.

  14. Online Randomizer

    List randomizer and random order generator. Input a list of numbers, letters, words, IDs, names, emails, or anything else and the randomizer will return the items in random order. Random list generator to randomly shuffle any list. List shuffler with true randomness (CPRNG). Maximum list length for the randomiser is 100,000 items.

  15. Generate Random Numbers in Python • datagy

    March 2, 2022 In this tutorial, you'll learn how to generate random numbers in Python. Being able to generate random numbers in different ways can be an incredibly useful tool in many different domains. Python makes it very easy to generate random numbers in many different ways.

  16. RANDOM.ORG

    There is also the Sequence Generator, which generates randomized sequences (like raffle tickets drawn from a hat) and where each number can only occur once. This page allows you to generate random integers using true randomness, which for many purposes is better than the pseudo-random number algorithms typically used in computer programs.

  17. Random 5 Digit Number Generator

    Generate a list of 5 digit random numbers with this random number generator . No sign up needed to use this app. Simply click on the generate button to get a list of random 5 digit numbers. Generate Random 5 Digit Numbers Number of output: Generate Numbers Sharing is Caring Check out other Number Generators Random 2 digit Number generator

  18. Random number generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome ...

  19. Random 5 Digit Number Generator

    5 digit number generator online tool allows you to randomly generate a list of five digit numbers. 2 Digit 3 Digit 4 Digit 5 Digit 6 Digit 7 Digit 8 Digit 9 Digit 10 Digit 11 Digit 12 Digit 13 Digit 14 Digit 15 Digit 16 Digit Input Quantity: 98510 26853 48130 20911 61102 43216 81104 23249 88460 00291 35435 92236

  20. 5 Ways to Generate Random Numbers in Excel

    Syntax for the RAND Function = RAND ( ) This function has no required or optional arguments. The function is always entered with an empty set of parenthesis. This function will generate a decimal random number between 0 and 1, but not including 0 or 1.

  21. Fantasy 5 Number Generator

    Use the Fantasy 5 Number Generators below if you're looking for a set of numbers to enter into the next draw. All you need to do is hit the 'Generate' button and a random set will appear straight away. It's fast, easy and the perfect method if you're not sure which numbers you want to play. It also allows you to see your selections ...

  22. 5-Digit Random Unique Numbers [500 Counts] ― JustinTOOLs.com

    Use this tool form to generate a list of unique (non-repeating) randomly ordered N-digit numbers. This app won't produce a repeat or duplicate numbers. Maximum digit is 18, the lowest is 1. Maximum total numbers, count or quantity is 1000. After generating a list of random numbers, click the "click to copy numbers" button or highlight and copy ...

  23. C++ Random Number Generator: Secrets for Robust Code

    5. Generate Random Number. After setting up your engine and distribution, the next step is the exciting part. It's like having all the ingredients for a recipe ready, and now it's time to cook! You'll use the engine and distribution you previously set up to generate a random number. Here's a refresher on the pieces you should have:

  24. Florida Lotto results: Powerball jackpot grows. 2 win Fantasy 5. Publix

    With Florida Lotto, every ticket purchased includes a randomly generated "multiplier" number that automatically increases non-jackpot cash prizes by two, three, four, five or 10 times. All Florida ...

  25. KFF Health Tracking Poll February 2024: Voters on Two Key Health Care

    Phone numbers used for the prepaid cell phone component were randomly generated from a cell phone sampling frame with disproportionate stratification aimed at reaching Hispanic and non-Hispanic ...

  26. Vice lays off hundreds, will cease publishing at Vice.com

    Vice is laying off hundreds of staff and will no longer publish at Vice.com. The outcome of the company's spectacular rise (it was valued at more than $5bn in 2017) and fall was revealed in a note ...