What is Binomial distribution and how to simulate it in Python

A binomial distribution is a discrete random variable that uses the formula and specifies the probability of each possible value. It is the discrete random distribution.

Properties of binomial distribution:

  1. The experiments consist of n repeated trials.
  2. Each trial can result in two possible outcomes.
  3. The probability of success expressed by P is the same on each trial.
  4. The trail is independent, which means the one trail does not affect the other trails.

Let’s understand Binomial Distribution with an example

T=tail, H=head


Suppose two coins are tossed, the outcomes are [HH, HT, TH, TT]

XOutcomesP(X=x)
Chances of HeadHHonly 1 time
Chances of Head-TailTH, HTtwo times
Chances of TailTTone time
  • so here the chances of the head are 25%,
  • the head-tail is 50%
  • and the tail is 25%.
  • this rule follows the binomial distribution.
  • Hence the formula is P(X=x). 
  • we can calculate this with the help of the formula P(X=x).

For example, one dice was throw that contains six sides, and the probability is printed as the output is

A real-life example of Binomial distribution

  1. The number of patients who test positive for corona by 1000 checkups.
  2. The number of defective items in 1 carton.
  3. How many times India win the match in a season.
  4. The daily sales of mobile on Amazon.

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