Uniform distribution is a uniform base distribution where all the outcomes have the same probability, which means that each result has the same opportunity to occur.
The above illustration gives a graphical representation of a coin toss. In a coin toss, we have an equal probability of getting a tail or a head.
As we can see in the graph, both sides of the coin have a 50% chance. As both sides of the coin have the same probability, it is an excellent example of uniform distribution.
Other than the graphical representation, we have a code implementation below in javascript which shows the number of tails and heads we get from randomly generating 0s and 1s.
let headCount = 0;let tailCount = 0;let tex = "";for (var i = 0; i < 100; i++) {let occ = Math.floor(Math.random() * 2);if (occ == 0){tex = tex + "head ";headCount++;}else{tex = tex + "tail ";tailCount++;}}console.log(tex);console.log("Total number of Tails = " + tailCount);console.log("Total number of Heads = " + headCount);
Note: Every time we run the code, it will provide a different result, but both heads and tails have the same probability of occurring
Lines 5 - 15: We used a for loop to emulate tossing a coin one hundred times. For the result of the toss, we used Math.random
to find a random number between 0,1. We treat 0 as the head and 1 as the tail.
Roll a die
When you roll a die, what is the probability of getting 3?
20%
16.67%
25%
15%
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