Random generation. Excel Random Number Generator in Functions and Data Analysis
A clear and convenient online number generator, which is used in Lately popularity. Received the greatest distribution during the drawing of prizes in social networks, among users.
It is also popular in other areas. Also we have or passwords and numbers.
Our random number generator online.
Our randomizer generator does not require you to download it to your personal PC. Everything happens in the online number generator mode. Just specify parameters such as: a range of online numbers in which numbers will be randomly selected. Also specify the number of numbers to be selected.
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Random number generator
Our random number generator randomly selects numbers completely randomly. It doesn't matter what day or hour you have on your computer. This is a real blind choice. The random generator simply shuffles all the numbers randomly. And then randomly chooses from them the number of random numbers you specified. Sometimes the numbers can be repeated, which proves the complete randomness of the random number generator.
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We have a sequence of numbers, consisting of almost independent elements that obey a given distribution. Usually evenly distributed.
You can generate random numbers in Excel in different ways and ways. Let's take a look at the best of them.
Random Number Function in Excel
- The RAND function returns a random uniformly distributed real number. It will be less than 1, greater than or equal to 0.
- The RANDBETWEEN function returns a random integer.
Let's look at their use with examples.
Selecting random numbers with RAND
This function does not require any arguments (RAND()).
To generate a random real number between 1 and 5, for example, use the following formula: =RAND()*(5-1)+1.
The returned random number is evenly distributed over the interval .
Each time the worksheet is calculated, or the value in any cell in the worksheet changes, a new random number is returned. If you want to save the generated population, you can replace the formula with its value.
- We click on a cell with a random number.
- Highlight the formula in the formula bar.
- Press F9. AND ENTER.
Let's check the uniformity of the distribution of random numbers from the first sample using the distribution histogram.
The range of vertical values is frequency. Horizontal - "pockets".
RANDBETWEEN function
The syntax of the RANDBETWEEN function is (lower bound; upper bound). The first argument must be less than the second. Otherwise, the function will throw an error. The bounds are assumed to be integers. The formula discards the fractional part.
An example of using the function:
Random numbers with 0.1 and 0.01 precision:
How to make a random number generator in Excel
Let's make a random number generator with the generation of a value from a certain range. We use a formula like: =INDEX(A1:A10;INTEGER(RAND()*10)+1).
Let's make a random number generator in the range from 0 to 100 with a step of 10.
From the list text values you need to choose 2 random. Using the RAND function, we compare text values in the range A1:A7 with random numbers.
Let's use the INDEX function to select two random text values from the original list.
To select one random value from the list, apply the following formula: =INDEX(A1:A7,RANDBETWEEN(1,COUNT(A1:A7))).
Normal Distribution Random Number Generator
The functions RAND and RANDBETWEEN produce random numbers with a single distribution. Any value with the same probability can fall into the lower limit of the requested range and into the upper one. It turns out a huge spread from the target value.
Normal distribution means that most of the generated numbers are close to the target. Let's correct the RANDBETWEEN formula and create a data array with a normal distribution.
The cost of goods X is 100 rubles. The entire batch produced is subject to a normal distribution. The random variable also follows a normal probability distribution.
Under such conditions, the average value of the range is 100 rubles. Let's generate an array and build a graph with a normal distribution with a standard deviation of 1.5 rubles.
We use the function: =NORMINV(RAND();100;1.5).
Excel calculated which values are in the range of probabilities. Since the probability of producing a product with a cost of 100 rubles is maximum, the formula shows values close to 100 more often than the rest.
Let's move on to plotting. First you need to create a table with categories. To do this, we divide the array into periods:
Based on the data obtained, we can form a diagram with a normal distribution. The value axis is the number of variables in the interval, the category axis is the periods.
Online number generator is a fairly simple and convenient auxiliary service for determining a sequence of random numbers. “Numbers rule the world,” Pythagoras once said. Even in ancient times, people believed in the magic of numbers. Thus, the science of numerology was born. Numbers bring people both joys and sorrows.
We have developed a random number generator so that it will certainly make every user happy.
Content:
What is the random selection program based on?
Random - translated from English as "random". Very often, by magical coincidence, unintentionally selected numbers turn out to be a number lottery ticket, your number in the list of contest participants.
Where is random selection used?
Numerical randomness has become widespread:
in the lottery business
among fans of casinos, hippodromes, various sports competitions
in the conduct of social competitions. networks
Online random number drawing ensures a fair selection of the winner.
Using our service in lotteries, you can participate in such projects as Gosloto 5 out of 36, 7 out of 49, Stoloto and others. Casino lovers will also appreciate our online generator.
Unfortunately, the human brain is often able to duplicate information, sometimes it is difficult to come up with a new combination. The random number generator will tell you how to win the coveted prize.
How to choose a number generator
There are many similar services offered online, but there are 5 reasons to choose a RNG random number generator on the Supergenerators website:
- simplicity and ease of use
- wide range of numbers
- convenience of the mobile version
- no specific link to social networks
- clear instructions, specific interface
4 steps to success with our randomizer:
- Designate the numerical range in which you want to get a sample
- Determine the desired number of output numbers
- Click the "Generate" button
- Copy the received answer and jump to the ceiling for joy!
With the Super Number Generator, there will be more successful moments in your life!
Thank you for choosing our free online service.
Always happy to help you and your friends!
Various lotteries, drawings, etc. are often held in many groups or publics on social networks, Instagram, etc., and are used by account owners to attract a new audience to the community.
The result of such draws often depends on the luck of the user, since the recipient of the prize is determined randomly.
For such a determination, draw organizers almost always use an online random number generator or a pre-installed one that is distributed free of charge.
Choice
Quite often, it can be difficult to choose such a generator, since their functionality is quite different - for some it is significantly limited, for others it is quite wide.
A fairly large number of such services are being implemented, but the difficulty is that they differ in scope.
Many, for example, are tied by their functionality to a certain social network(for example, many generator applications on VKontakte only work with links from this social network).
The simplest generators simply generate a random number within a given range.
This is convenient because it does not associate the result with a specific post, which means that they can be used for draws outside the social network and in various other situations.
They don't really have any other use.
<Рис. 1 Генератор>
Advice! When choosing the most suitable generator, it is important to consider the purpose for which it will be used.
Specifications
For the fastest process of choosing the optimal online random number generation service, the table below shows the main specifications and functionality of such applications.
| Name | Social network | Multiple results | Select from a list of numbers | Online Widget for Website | Select from a range | Turn off repetitions |
|---|---|---|---|---|---|---|
| randstuff | Yes | Yes | No | Yes | No | |
| Cast Lots | Official site or VKontakte | No | No | Yes | Yes | Yes |
| Random number | Official site | No | No | No | Yes | Yes |
| Randomus | Official site | Yes | No | No | Yes | No |
| random numbers | Official site | Yes | No | No | No | No |
All applications discussed in the table are described in more detail below.
<Рис. 2 Случайные числа>
randstuff
<Рис. 3 RandStuff>
You can use this application online using the link to its official website http://randstuff.ru/number/.
This is a simple random number generator, characterized by fast and stable operation.
It is successfully implemented both in the format of a separate independent application on the official website, and as an application in the VKontakte social network.
The peculiarity of this service is that it can choose a random number both from the specified range and from a specific list of numbers that can be specified on the site.
Pros:
- Stable and fast work;
- Lack of direct link to the social network;
- You can select one or more numbers;
- You can only choose from the given numbers.
Minuses:
- The impossibility of holding a draw on VKontakte (this requires a separate application);
- Applications for VKontakte do not run in all browsers;
- The result sometimes seems predictable, since only one calculation algorithm is used.
User reviews about this application are as follows: “We determine the winners in VKontakte groups through this service. Thank you”, “You are the best”, “I use only this service”.
Cast Lots
<Рис. 4 Cast Lots>
This application is a simple function generator, implemented on the official website, in the form of a VKontakte application.
There is also a generator widget to embed on your site.
The main difference from the previous described application is that this allows you to disable the repetition of the result.
That is, when conducting several generations in a row in one session, the number will not repeat.
- The presence of a widget to insert on a website or blog;
- Ability to disable the repetition of the result;
- The presence of the function "even more randomness", after the activation of which the selection algorithm changes.
Negative:
- The impossibility of determining several results at once;
- Inability to select from a specific list of numbers;
- To select a winner in public, you must use a separate VKontakte widget.
User reviews are as follows: “It works stably, it is quite convenient to use”, “Convenient functionality”, “I use only this service”.
Random number
<Рис. 5 Случайное число>
This service is located at http://random number.rf/.
A simple generator with minimum of functions and additional features.
Can randomly generate numbers within a given range (maximum from 1 to 99999).
The site does not have any graphic design, and therefore the page is easy to load.
The result can be copied or downloaded with the click of a button.
Negative:
- No widget for VKontakte;
- There is no possibility of holding draws;
- There is no way to insert the result into a blog or website.
Here's what users say about this service: "A good generator, but not enough functions", "Very few features", "Suitable for quickly generating a number without unnecessary settings."
Randomus
<Рис. 6 Рандомус>
You can use this random number generator at http://randomus.ru/.
Another simple one, but functional random number generator.
The service has sufficient functionality for determining random numbers, however, it is not suitable for holding draws and other more complex processes.
Negative:
- The impossibility of holding draws based on post reposts, etc.
- There is no application for VKontakte or a widget for the site;
- It is not possible to disable repeating results.
Have you ever wondered how Math.random() works? What is a random number and how is it obtained? And imagine a question at an interview - write your random number generator in a couple of lines of code. And so, what is it, an accident and is it possible to predict it?
I am very fascinated by various IT puzzles and puzzles, and the random number generator is one of such puzzles. Usually in my telegram channel I sort out all sorts of puzzles and various tasks from interviews. The problem about the random number generator has gained great popularity and I wanted to perpetuate it in the depths of one of the authoritative sources of information - that is, here on Habré.
This material will be useful to all those front-end developers and Node.js developers who are at the forefront of technology and want to get into the blockchain project / startup, where questions about security and cryptography, at least on basic level, even front-end developers are asked.
Pseudo random number generator and random number generator
In order to get something random, we need a source of entropy, a source of some kind of chaos from which we will use to generate randomness.This source is used to accumulate entropy and then obtain from it the initial value (initial value, seed), which is necessary for random number generators (RNG) to generate random numbers.
The Pseudo-Random Number Generator uses a single seed value, hence its pseudo-randomness, while the Random Number Generator always generates a random number, starting with a high-quality random value that is taken from various sources of entropy.
Entropy - is a measure of disorder. Information entropy is a measure of the uncertainty or unpredictability of information.It turns out that in order to create a pseudo-random sequence, we need an algorithm that will generate some sequence based on a certain formula. But such a sequence can be predicted. However, let's imagine how we could write our own random number generator if we didn't have Math.random()
PRNG has some algorithm that can be reproduced.
RNG - is getting numbers completely from any noise, the ability to calculate which tends to zero. At the same time, the RNG has certain algorithms for leveling the distribution.
Inventing our own PRNG algorithm
Pseudo-random number generator (PRNG) is an algorithm that generates a sequence of numbers whose elements are almost independent of each other and obey a given distribution (usually uniform).We can take a sequence of some numbers and take the modulus of the number from them. The simplest example that comes to mind. We need to think about what sequence to take and the module from what. If just directly from 0 to N and module 2, then you get a generator of 1 and 0:
Function* rand() ( const n = 100; const mod = 2; let i = 0; while (true) ( yield i % mod; if (i++ > n) i = 0; ) ) let i = 0; for (let x of rand()) ( if (i++ > 100) break; console.log(x); )
This function generates for us the sequence 01010101010101 ... and it cannot even be called pseudo-random. For a generator to be random, it must pass the test for the next bit. But we do not have such a task. Nevertheless, even without any tests, we can predict the next sequence, which means that such an algorithm is not suitable in the forehead, but we are in the right direction.
But what if we take some well-known, but non-linear sequence, for example, the number PI. And as a value for the module, we will take not 2, but something else. You can even think about the changing value of the module. The sequence of digits in Pi is considered random. The generator can work using pi starting from some unknown point. An example of such an algorithm, with a PI-based sequence and modulo change:
Const vector = [...Math.PI.toFixed(48).replace(".","")]; function* rand() ( for (let i=3; i<1000; i++) {
if (i >99) i = 2; for (let n=0; n
We got a number generator from 0 to 9, but the distribution is very uneven and it will generate the same sequence every time.
We can take not the number Pi, but the time in numerical representation and consider this number as a sequence of digits, and in order to prevent the sequence from repeating each time, we will read it from the end. In total, our algorithm for our PRNG will look like this:
Function* rand() ( let newNumVector = () => [...(+new Date)+""].reverse(); let vector = newNumVector(); let i=2; while (true) ( if ( i++ > 99) i = 2; let n=-1; while (++n< vector.length) yield (vector[n] % i);
vector = newNumVector();
}
}
// TEST:
let i = 0;
for (let x of rand()) {
if (i++ >100) break; console.log(x) )
Now it looks like a pseudo-random number generator. And the same Math.random() - is a PRNG, we'll talk about it a little later. Moreover, each time the first number is different.
Actually on these simple examples you can understand how more complex random number generators work. And there are even ready-made algorithms. For example, let's analyze one of them - this is the Linear Congruent PRNG (LCPRNG).
Linear congruent PRNG
Linear Congruential PRNG (LCPRNG) - is a common method for generating pseudo-random numbers. It does not have cryptographic strength. This method consists in calculating the terms of a linear recurrent sequence modulo some natural number m given by a formula. The resulting sequence depends on the choice of the starting number - i.e. seed. At different meanings seed yields different sequences of random numbers. An example of the implementation of such an algorithm in JavaScript:Const a = 45; const c = 21; const m = 67; varseed = 2; const rand = () => seed = (a * seed + c) % m; for(let i=0; i<30; i++)
console.log(rand())
Many programming languages use LCPRNG (but not just such an algorithm (!).
As mentioned above, such a sequence can be predicted. So why do we need PRNG? If we talk about security, then PRNG is a problem. If we talk about other tasks, then these properties - can play a plus. For example, for various special effects and graphics animations, you may need to call random frequently. And here the distribution of values and performance are important! Security algorithms cannot boast of speed.
Another property - reproducibility. Some implementations allow you to specify a seed, which is very useful if a sequence is to be repeated. Reproduction is necessary in tests, for example. And there are many other things that do not require a secure RNG.
How Math.random() works
The Math.random() method returns a pseudo-random floating point number from the range = crypto.getRandomValues(new Uint8Array(1)); console log(rvalue)
But, unlike PRNG Math.random(), this method is very resource intensive. The fact is that this generator uses system calls in the OS to access entropy sources (poppy address, cpu, temperature, etc ...).
