Uniform Distribution
The uniform distribution refers to a probability distribution in which all outcomes are equally likely. For example, rolling a fair die produces uniform distribution over numbers 1 to 6.
The distribution is characterized by two parameters  a and b denoting the start and end of the distribution range. All numbers between a and b are equally probable.
Uniform distribution is useful as a simple null hypothesis for probability. It represents complete uncertainty about the distribution.
Solution
Here is how to generate random numbers from a uniform distribution:
Java


C++


Python


Uniform distribution provides equal probability over a range of values.
Description: Uniform Distribution
Uniform Distribution is a type of probability distribution in which all outcomes are equally likely. In a discrete uniform distribution, each integer value has an equal chance of being picked. In a continuous uniform distribution, any value between the given minimum and maximum is equally likely to occur. It is characterized by two parameters: the minimum value (a
) and the maximum value (b
).
Solution:
Generating random numbers with a uniform distribution is quite common in programming. Here’s how to do it in Java, C++, and Python.
Java
Java’s Random
class can be used to generate uniformly distributed random numbers.


C++
C++’s <random>
library provides ways to generate uniformly distributed random numbers.


Python
Python’s random
module provides a function to generate uniformly distributed numbers.


Key Takeaways:
 Uniform distribution is when all outcomes have an equal chance of occurring.
 Java, C++, and Python all provide builtin methods to generate uniformly distributed random numbers.
 The range of the distribution is defined by its minimum (
a
) and maximum (b
) values.