Distribution of Random Numbers in JavaScript
The Issue with Math.ceil(Math.random())
π€
In JavaScript, generating random numbers is a common task, but itβs crucial to understand the distribution of these numbers to ensure fairness and accuracy in applications. A frequently encountered solution is using Math.ceil(Math.random())
, but this approach has its pitfalls.
Why Math.ceil(Math.random())
is Problematic π«

Bias Towards 1:
Math.random()
generates a number ranging from 0 (inclusive) to 1 (exclusive), typically very close to 0. WhenMath.ceil()
is applied to this, the number is rounded up to the nearest integer. This process makes the occurrence of 1 slightly more likely than other numbers. 
Possibility of Zero: Although rare,
Math.random()
can return 0. In this case,Math.ceil(0)
will still yield 0. This behavior contradicts the expectation of generating a number between 1 and 100.
A Better Approach β
To achieve a more evenly distributed range of random numbers, itβs advisable to use Math.floor(Math.random() * 100) + 1
. This method ensures:
 Uniform Distribution: Each number from 1 to 100 has an equal chance of occurrence.
 No Zeroes: The range strictly stays between 1 and 100, as intended.
Code Example π»
function generateRandomNumber() {
return Math.floor(Math.random() * 100) + 1
}
This function will consistently give you a random number between 1 and 100 with a uniform distribution.
Conclusion π
While Math.ceil(Math.random())
might seem like a straightforward solution for random number generation, it introduces a slight bias and the possibility of zero, which might not be desirable. For a better distribution and reliability, Math.floor(Math.random() * 100) + 1
is the way to go.
Understanding these nuances is key to effective programming in JavaScript, especially when dealing with randomness and its implications.