Use this random generator to get a truly random, cryptographically safe number. It generates random numbers that can be used where unbiased randomization is needed such as when drawing numbers for a lottery, raffle, giveaway, or sweepstake. An RNG draw can also be used for determining who goes first in a game, and so on.

Quick navigation:

- How to pick a random number between two numbers?
- Where are random numbers useful?
- Generating a random number

- Sources of randomness

## How to pick a random number between two numbers?

You can use this random number generator to pick a truly random number between any two numbers. For example, to get a **random number between 1 and 10**, including 10, enter 1 in the first field and 10 in the second, then press "Get Random Number". Our 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. To perform the equivalent of a **coin flip**, set the range between 1 and 2 and the random selector will pick a number between 1 and 2.

To generate more than one unique number (meaning there are no repeats), just select how many you need from the drop-down below. For example, selecting to draw 6 numbers out of the set of 1 to 49 possible would be equivalent to simulating a lottery draw for a game with these parameters.

## Where are random numbers useful?

You might be organizing a charity lottery, a giveaway, a raffle, a sweepstakes, etc. and you need to draw a winner - this generator is for you! It is **completely unbiased and outside of your control**, so you can assure your crowd of the fairness of the draw, which might not be true if you are using standard methods like rolling a dice. If you need to choose several among the participants instead, just select the number of unique numbers you want generated by our random number picker and you are all set. However, it is usually best to draw the winners one after another, to keep the tension for longer (discarding repeat draws as you go).

A random number generator is also useful if you need to decide **who goes first** in some game or activity, such as board games, sport games and sports competitions. The same is true if you need to decide the **participation order** for multiple players / participants. Picking a team at random or randomizing a list of participants also depends on randomness.

Nowadays, a number of government-run and private lotteries and lottery games are using software RNGs to pick a number instead of more traditional drawing methods. RNGs are also used to determine the outcomes of all modern slot machines. For some other modern applications, see How Random Numbers Are the Driving Force Behind Video Games, Jury Selection, and More.

Finally, random numbers are also useful in statistics and simulations. In statistical applications one often needs to draw numbers randomly from distributions different than the uniform, e.g. a normal distribution, binomial distribution, power distribution, pareto distribution... For such use-cases a more sophisticated software is required to perform the draw.

## Generating a random number

There is a philosophical question about **what exactly "random" is**, but its defining characteristic is surely **unpredictability**. We cannot talk about the unpredictability of a single number, since that number is just what it is, but we can talk about the unpredictability of a series of numbers (number sequence). If a sequence of numbers is random, then you should not be able to predict the next number in the sequence while knowing any part of the sequence so far. Examples for this are found in rolling a fair dice, spinning a well-balanced roulette wheel, drawing balls from a sphere, and the classic **flip of a coin**. No matter how many dice rolls, coin flips, roulette spins or lottery draws you observe, you do not improve your chances of guessing the next number in the sequence. For those interested in physics the classic example of random movement is the Browning motion of gas or fluid particles.

Given the above and knowing that computers are fully deterministic, meaning that their output is completely determined by their input, one might say that we cannot generate a random number with a computer. However, one will only partially be correct, since a dice roll or a coin flip is also deterministic, if you know the state of the system.

The randomness in our number generator comes from physical processes - our server gathers environmental noise from device drivers and other sources into an **entropy pool**, from which random numbers are created ^{[1]}.

### Sources of randomness

According to Alzhrani & Aljaedi ^{[2]} there are four sources of randomness that are used in the seeding of a generator of random numbers, two of which are used in our number picker:

- Entropy from the disk when the drivers call it - gathering seek time of block layer request events.
- Interrupt events from USB and other device drivers
- System values such as MAC addresses, serial numbers and Real Time Clock - used only to initialize the input pool, mostly on embedded systems.
- Entropy from input hardware - mouse and keyboard actions (not used)

This puts the RNG we use in this randomizer in compliance with the recommendations of RFC 4086 on randomness required for security ^{[3]}.

## True random versus pseudo random number generators

A **pseudo-random number generator (PRNG)** is a finite state machine with an initial value called the **seed** ^{[4]}. Upon each request to draw a number at random, a transaction function computes the next internal state and an output function produces the actual number based on the state. A PRNG deterministically produces a periodic sequence of values that depends only on the initial seed given. An example would be a linear congruential generator like PM88. Thus, knowing even a short sequence of generated values it is possible to figure out the seed that was used and thus - know the next value.

A **cryptographic pseudo-random number generator (CPRNG)** is a PRNG in that it is predictable if the internal state is known. However, assuming the generator was seeded with sufficient entropy and the algorithms have the needed properties, such generators will not quickly reveal significant amounts of their internal state, meaning that you would need a huge amount of output before you can mount a successful attack on them. Randomizers of this type are suitable if the number drawing generator is to be used in a high stakes situation.

A hardware RNG is based on an unpredictable physical phenomenon, referred to as **"entropy source"**. Radioactive decay, or more precisely the points in time at which a radioactive source decays is a phenomenon as close to randomness as we know, while decaying particles are easy to detect. Another example is heat variation - some Intel CPUs have a detector for thermal noise in the silicon of the chip that outputs random numbers.

Hardware RNGs are, however, often biased and, more importantly, limited in their capacity to generate sufficient entropy in practical spans of time, due to the low variability of the natural phenomenon sampled. Thus, another type of RNG is needed for practical applications: a **true random number generator** (TRNG). In it cascades of hardware RNGs (entropy harvester) are used to periodically reseed a PRNG. When the entropy is sufficient, it behaves as a TRNG. This is the type of process used to generate random numbers in this tool.

#### References

[1] Linux manual page on "urandom"

[2] Alzhrani K., Aljaedi A. (2015) "Windows and Linux Random Number Generation Process: A Comparative Analysis", *International Journal of Computer Applications* 113:21

[3] Schiller J., Crocker S. (2005) "IETF RFC 4086 - Randomness Requirements for Security"

[4] Goichon F., Lauradoux C., Salagnac G., Vuillemin T. (2012) "A study of entropy transfers in the Linux Random Number Generator", research report 8060

## FAQs

### Is there a true random number generator? ›

True Random Number Generators

**A true random number generator — a hardware random number generator (HRNG) or true random number generator (TRNG)** — is cryptographically secure and takes into account physical attributes such as atmospheric or thermal conditions. Such tools may also take into account measurement biases.

**What is the luckiest number between 1 and 200? ›**

1, 3, 7, 9, 13, 15, 21, 25, 31, 33, 37, 43, 49, 51, 63, 67, 69, 73, 75, 79, 87, 93, 99, 105, 111, 115, 127, 129, 133, 135, 141, 151, 159, 163, 169, 171, 189, 193, 195, 201, 205, 211, 219, 223, 231, 235, 237, 241, 259, 261, 267, 273, 283, 285, 289, 297, 303, 307, 319, 321, 327, ... (sequence A000959 in the OEIS).

**Is random () really random? ›**

Random is random, right? **Not really**. Since computers have no imagination whatsoever, it is physically impossible for them to come up with a truly random number. If you use built-in functions to randomize a number, it will produce a pseudo-random number using a complex algorithm.

**What is the most picked number between 1 and 100? ›**

The most random two-digit number is **37**, When groups of people are polled to pick a “random number between 1 and 100”, the most commonly chosen number is 37.

**How do you find a truly random number? ›**

For truly random numbers, **the computer must use some external physical variable that is unpredictable, such as radioactive decay of isotopes or airwave static, rather than by an algorithm**. At the quantum level, subatomic particles have completely random behavior, making them ideal variables of an unpredictable system.

**Why is 17 the most common random number? ›**

Seventeen is: Described at MIT as 'the least random number', according to the Jargon File. This is supposedly because **in a study where respondents were asked to choose a random number from 1 to 20, 17 was the most common choice**. This study has been repeated a number of times.

**Which number is best for lottery? ›**

**The most common Mega Ball number is 22**. Meanwhile, stay clear of 21, 45, 50, 55, and 51 when choosing your first five numbers. (But keep in mind that the unlucky and lucky lottery numbers and their exact number of calls are always changing!)

**What number is good for wealth? ›**

**Money number 6** in numerology

Considered to be the money attracting number, people falling under this will have the most luck when it comes to monetary wealth.

**Which number is lucky for lottery? ›**

India is known for having several lucky numbers. These are **7,8,9,13 and 108**. There are a lot of online websites to play the lottery where you can try your chance.

**Why is true randomness impossible? ›**

Randomness is relational. The problem modern computers have with randomness is that **it doesn't make mathematical sense**. You can't program a computer to produce true randomness—wherein no element has any consistent, rule-based relationship to any other element—because then it wouldn't be random.

### Can random numbers be predicted? ›

Surprisingly, **the general-purpose random number generators that are in most widespread use are easily predicted**. (In contrast RNGs used to construct stream ciphers for secure communication are believed to be infeasible to predict, and are known as cryptographically secure).

**What is the most common random number between 1 and 10? ›**

According to the video, if you ask people to randomly pick any one integer between 1 and 10 (both inclusive), people are more likely to choose **7**.

**What is the rarest number? ›**

← 6173 6174 6175 → | |
---|---|

Senary | 44330_{6} |

Octal | 14036_{8} |

Duodecimal | 36A6_{12} |

Hexadecimal | 181E_{16} |

**Why do people always pick 7? ›**

But we also have religious reasons for thinking that 7 is special – think: **seven deadly sins and seventh heaven**. In nature, you have the seven wonders of the world, seven colours of the rainbow, seven seas and seven continents.

**Is it possible to get a truly random sample? ›**

To be a truly random sample, **every subject in your target population must have an equal chance of being selected in your sample**. An example of violating this assumption might be conducting a study to estimate the amount of time college students workout at your university each week.

**Is there a formula for random? ›**

If we wish to generate a random number between two numbers, we can use the formula: **RAND() * (b – a) + a**, where a is the smallest number and b is the largest number that we wish to generate a random number for.

**What is a random float number? ›**

random-float is **a mathematics primitive that reports a random floating point number anywhere between 0 and the given number**. For instance, random-float 10 could report 6.9105, 7, 4.2, 0.451, 0.0000001, 9.99999, etc. random-float is very useful in modeling phenomena that require continuous numbers.

**What is the luckiest number in the world? ›**

**Seven** was the most popular choice for both men and women. The survey revealed some other findings, too.

**Why is 70 a weird number? ›**

Weird numbers are natural numbers that are abundant but not semiperfect. For example, 70 is the lowest weird number, because **its set of proper divisors {1,2,5,7,10,14,35} sum to 74, but no subset of its set of proper divisors sum to the number 70**, and 70 is the smallest number to meet such conditions.

**What type of number is 1? ›**

**Whole Numbers**

{0, 1, 2, 3, 4…..} These include the natural (counting) numbers, but they also include zero.

### Which lottery is easiest to win? ›

The lottery with the best odds in the world, for a major jackpot, is the **Spanish Christmas Lottery, known as El Gordo ('The Fat One')** at the outstanding odds of 1 in 100,000. However, this lottery is actually more like a raffle.

**Is there a trick to win the lottery? ›**

Lottery experts agree that the number one way to boost your chance of getting a winning ticket is to just **get more tickets**. Even though the probability of winning the lottery is low in general, the greater the amount of tickets you have, the more likely it is that one of these tickets will be the winner.

**What angel number is lucky? ›**

**777 or 7777**

Seven is as lucky in angel numbers as it is at the casino! Experiencing seven as an angel number (either within a set of three, four, or within a pattern) means that good fortune — especially finance-wise — could be on the way.

**What does 777 mean? ›**

According to Berry, seeing 7, 77, and 777 is **your guardian angel's way of telling you to stay strong and to continue moving forward on your journey — even through changes and obstacles**. "The path ahead can become challenging, but the message is to keep a positive outlook in order to overcome anything," Berry says.

**What are the 3 luckiest numbers? ›**

The top 10 are: **11, 7, 17, 27,19, 23, 12,13, 9 and 18**. So how do you pick lucky numbers? For those who use birthdays, five of the most commonly drawn numbers are more than 31, meaning they are not likely to have picked them. Another approach that is commonly used is to look for numbers that have not come up in a while.

**What are the luckiest lottery numbers for 2022? ›**

**Here are the white Mega Millions numbers that were drawn the most in 2022:**

- Drawn 16 times: 38.
- Drawn 12 times: 7,15,64.
- Drawn 11 times: 3, 6, 11, 16, 21.

**What are lucky numbers for 2022? ›**

**Astrological Lucky Numbers and Horoscope of Lucky Zodiac Signs In 2022**

- ARIES- The lucky numbers are - 9, 41, 47, 49, 60, 67. ...
- TAURUS- The lucky numbers are- Lucky numbers: 14, 18, 22, 31, 37, 51. ...
- GEMINI- The lucky numbers are 4, 5, 11, 19, 52, 68. ...
- CANCER- ...
- LEO- ...
- VIRGO- ...
- LIBRA- ...
- SCORPIO-

**What did Einstein say about randomness? ›**

“**I, at any rate, am convinced that He is not playing at dice**,” Albert Einstein wrote to his colleague Max Born in December 1926. Repeated over the years, his sound bite became the quintessential put-down of quantum mechanics and its embrace of randomness.

**Is there a proof for randomness? ›**

**No, there is no such prove** - if you have perfectly random numbers, the probability of each sequence of length n is equal. However, there are statistical tests to asses the quality of a random number generator, which is probably what you are looking for. See Diehard tests.

**What is the best random number generator? ›**

**The 10 Best Online Random Number Generators**

- RandomNumberGenerator.org. ...
- Random Number Generator. ...
- Number Generator. ...
- GIGAcalculator Random Number Generator. ...
- CalculatorSoup Random Number Generator. ...
- Math Goodies Official Random Number Generator. ...
- Random Result. ...
- Stat Trek Random Number Generator.

### Can math random ever be 1? ›

The Math. random() method returns a random number from 0 (inclusive) up to but **not including 1 (exclusive)**.

**Can a random number generator be manipulated? ›**

With some random number generators, **it's possible to select the seed carefully to manipulate the output**. Sometimes this is easy to do. Sometimes it's hard but doable. Sometimes it's theoretically possible but practically impossible.

**Is math random ever 0? ›**

**Math.** **random() can never generate 0 because it starts with a non-zero seed**. Set the seed to zero, the function does not work, or throws an error. A random number generator always returns a value between 0 and 1, but never equal to one or the other.

**What is the lucky number of God? ›**

**7**: The number seven in the Bible is considered one of the most powerful and lucky numbers in scripture, according to the practice of gematria. Seven refers to the Creation of the world, accomplished by God in seven days according to Genesis.

**What number do most people choose from 1 to 10? ›**

Exploited in carnivals, the fact that given a choice of any number between 1 and 10, people will most often choose **3 or 7**.

**What's the least popular number? ›**

More than any other number, people seemed to pick 0 because they thought it was a clever thing to do, Bellos says. As for the world's “least favorite” number, that would be **110**.

**Is true random sampling possible? ›**

A truly random sample involves a selection from the target population. Ideally, this is taking the population, randomly picking some participants, and they all agree to participate. This is **almost impossible**. Getting everybody to agree or be available doesn't happen very often.

**How does a true random number generator work? ›**

A true random number generator (TRNG), also known as a hardware random number generator (HRNG), does not use a computer algorithm. Instead, it **uses an external unpredictable physical variable such as radioactive decay of isotopes or airwave static to generate random numbers**.

**Is perfect randomness possible? ›**

Such a result is impossible in any conceivable universe. Team E would argue that **perfect randomness and objective probabilities are logical impossibilities**. We should not accept them, but instead try to find physical mechanisms that can explain the observed results, no matter what current physical laws they break.

**What is lottery method? ›**

With a lottery method, **each member of the population is assigned a number, after which numbers are selected at random**. An example of a simple random sample would be the names of 25 employees being chosen out of a hat from a company of 250 employees.

### What is an infinite sample? ›

A random sample from an infinite population is therefore considered as **a random sample from a distribution**. This means that there is an underlying distribution governing the random sample, typically making some values more likely than others, according to the shape of the distribution.

**Why are true random samples rarely used? ›**

In practice, very few research studies use “true” random sampling because **it is usually not feasible to ensure that all individuals in the population have an equal chance of being selected**.

**How is true randomness tested? ›**

**Specific tests for randomness**

- Linear congruential generator and Linear-feedback shift register.
- Generalized Fibonacci generator.
- Cryptographic generators.
- Quadratic congruential generator.
- Cellular automaton generators.
- Pseudorandom binary sequence.

**What are the 4 types of random sampling? ›**

There are four primary, random (probability) sampling methods – **simple random sampling, systematic sampling, stratified sampling, and cluster sampling**.

**Can you manipulate a random number generator? ›**

With some random number generators, **it's possible to select the seed carefully to manipulate the output**. Sometimes this is easy to do. Sometimes it's hard but doable. Sometimes it's theoretically possible but practically impossible.