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Luca White
Luca White

JavaScript Math.random() Explained: Examples and Tips.


Math Random JavaScript: How to Generate Random Numbers in JS




Random numbers are useful for many purposes, such as generating test data, simulating games, creating passwords, and more. In this article, we will learn how to use the Math.random() method in JavaScript to generate random numbers, as well as some of its limitations and alternatives.


Introduction




What is Math.random() and why do we need it?




The Math object in JavaScript is a built-in object that has properties and methods for performing mathematical calculations. One of its methods is Math.random(), which returns a floating-point, pseudo-random number that's greater than or equal to 0 and less than 1, with approximately uniform distribution over that range.




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We need Math.random() because it allows us to generate random numbers that we can then scale or manipulate according to our desired range or format. For example, we can use Math.random() to get a random number between 0 and 100, or a random integer between 1 and 10, or a random hexadecimal color code, and so on.


How does Math.random() work and what does it return?




The Math.random() method works by using an algorithm that produces a sequence of numbers that appear to be random, but are actually deterministic and predictable. The algorithm uses an initial value called a seed, which is usually derived from the current time or some other source of randomness. The algorithm then applies some mathematical operations to the seed to generate the next number in the sequence, and so on.


The Math.random() method returns a number between 0 (inclusive) and 1 (exclusive), which means that 0 is a possible value but 1 is not. The number has up to 16 decimal digits of precision, depending on the implementation. The number can be positive or negative, depending on the sign bit of the binary representation.


Examples of using Math.random()




Getting a random number between 0 and 1




To get a random number between 0 and 1, we can simply call Math.random() without any parameters. For example:


// Get a random number between 0 and 1 let x = Math.random(); console.log(x); // e.g. 0.3749283749837498


Getting a random number between two values




To get a random number between two values, say min and max, we can use the following formula:


// Get a random number between min and max let x = Math.random() * (max - min) + min; console.log(x); // e.g. 5.48394839483948


This formula works by multiplying the result of Math.random() by the difference between max and min, which gives us a number between 0 and that difference. Then we add min to that number, which shifts it to the desired range. Note that this formula returns a number that is greater. or equal to min and less than max.


Getting a random integer between two values




To get a random integer between two values, say min and max, we can use the following formula:


// Get a random integer between min and max let x = Math.floor(Math.random() * (max - min)) + min; console.log(x); // e.g. 5


This formula works by applying the Math.floor() method to the result of the previous formula, which rounds it down to the nearest integer. Note that this formula returns an integer that is greater than or equal to min and less than max.


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Getting a random integer between two values, inclusive




To get a random integer between two values, say min and max, inclusive, we can use the following formula:


// Get a random integer between min and max, inclusive let x = Math.floor(Math.random() * (max - min + 1)) + min; console.log(x); // e.g. 6


This formula works by adding 1 to the difference between max and min, which ensures that max is also a possible value. Then we apply the Math.floor() method as before. Note that this formula returns an integer that is greater than or equal to min and less than or equal to max.


Limitations and alternatives of Math.random()




Math.random() is not cryptographically secure




One of the limitations of Math.random() is that it is not cryptographically secure, which means that it is not suitable for generating sensitive data such as passwords, encryption keys, tokens, etc. This is because the algorithm behind Math.random() is not random enough and can be predicted or manipulated by an attacker. For example, if an attacker knows the seed or the previous outputs of Math.random(), they can calculate the next outputs and guess the generated data.


Math.random() does not produce a uniform distribution




Another limitation of Math.random() is that it does not produce a uniform distribution of numbers, which means that some numbers are more likely to occur than others. This is because the algorithm behind Math.random() uses bitwise operations that introduce some bias in the output. For example, if we use Math.random() to generate a random number between 0 and 255, we will see that some numbers appear more frequently than others. This can affect the accuracy and fairness of our applications that rely on random numbers.


How to use crypto.getRandomValues() for secure random numbers




If we need to generate secure random numbers in JavaScript, we can use the window.crypto.getRandomValues() method, which is part of the Web Cryptography API. This method takes an array or a typed array as a parameter and fills it with cryptographically strong random values. For example:


// Get 16 secure random bytes let bytes = new Uint8Array(16); window.crypto.getRandomValues(bytes); console.log(bytes); // e.g. [216, 47, 173, 11, 128, 92, 237, 214, 36, 44, 21, 162, 194, 175, 111, 97]


How to use other libraries or algorithms for different distributions




If we need to generate random numbers with different distributions in JavaScript, such as normal, exponential, binomial, etc., we can use other libraries or algorithms that implement these distributions. For example, we can use the following libraries:


  • : A library that provides various methods for generating random numbers with different distributions and properties.



  • : A library that provides various methods for generating random data such as names, dates, colors, etc., as well as numbers with different distributions.



  • : A library that provides various methods for generating random numbers with different distributions using the D3.js library.



Alternatively, we can implement our own algorithms for generating random numbers with different distributions, such as the Box-Muller transform, the inverse transform method, the rejection method, etc. However, these algorithms may require more mathematical knowledge and coding skills, and may not be as efficient or accurate as the existing libraries.


Conclusion




Summary of the main points




In this article, we have learned how to use the Math.random() method in JavaScript to generate random numbers, as well as some of its limitations and alternatives. We have seen that:


  • Math.random() returns a floating-point, pseudo-random number between 0 and 1, with approximately uniform distribution.



We can use formulas to scale or manipulate the result of Math.random() to get random numbers between tw


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