Binomial Random Variables Last Updated : 10 Apr, 2025 Comments Improve Suggest changes Like Article Like Report In this post, we'll discuss Binomial Random Variables.Prerequisite : Random Variables A specific type of discrete random variable that counts how often a particular event occurs in a fixed number of tries or trials. For a variable to be a binomial random variable, ALL of the following conditions must be met: There are a fixed number of trials (a fixed sample size).On each trial, the event of interest either occurs or does not.The probability of occurrence (or not) is the same on each trial.Trials are independent of one another.Mathematical Notations n = number of trialsp = probability of success in each trialk = number of success in n trialsNow we try to find out the probability of k success in n trials.Here the probability of success in each trial is p independent of other trials. So we first choose k trials in which there will be a success and in rest n-k trials there will be a failure. Number of ways to do so is Since all n events are independent, hence the probability of k success in n trials is equivalent to multiplication of probability for each trial.Here its k success and n-k failures, So probability for each way to achieve k success and n-k failure is Hence final probability is (number of ways to achieve k success and n-k failures) *(probability for each way to achieve k success and n-k failure)Then Binomial Random Variable Probability is given by: Let X be a binomial random variable with the number of trials n and probability of success in each trial be p. Expected number of success is given by E[X] = npVariance of number of success is given by Var[X] = np(1-p)Example 1 : Consider a random experiment in which a biased coin (probability of head = 1/3) is thrown for 10 times. Find the probability that the number of heads appearing will be 5.Solution : Let X be binomial random variable with n = 10 and p = 1/3P(X=5) = ? Here is the implementation for the same C++ // C++ program to compute Binomial Probability #include <iostream> #include <cmath> using namespace std; // function to calculate nCr i.e., number of // ways to choose r out of n objects int nCr(int n, int r) { // Since nCr is same as nC(n-r) // To decrease number of iterations if (r > n / 2) r = n - r; int answer = 1; for (int i = 1; i <= r; i++) { answer *= (n - r + i); answer /= i; } return answer; } // function to calculate binomial r.v. probability float binomialProbability(int n, int k, float p) { return nCr(n, k) * pow(p, k) * pow(1 - p, n - k); } // Driver code int main() { int n = 10; int k = 5; float p = 1.0 / 3; float probability = binomialProbability(n, k, p); cout << "Probability of " << k; cout << " heads when a coin is tossed " << n; cout << " times where probability of each head is " << p << endl; cout << " is = " << probability << endl; } Java // Java program to compute Binomial Probability import java.util.*; class GFG { // function to calculate nCr i.e., number of // ways to choose r out of n objects static int nCr(int n, int r) { // Since nCr is same as nC(n-r) // To decrease number of iterations if (r > n / 2) r = n - r; int answer = 1; for (int i = 1; i <= r; i++) { answer *= (n - r + i); answer /= i; } return answer; } // function to calculate binomial r.v. probability static float binomialProbability(int n, int k, float p) { return nCr(n, k) * (float)Math.pow(p, k) * (float)Math.pow(1 - p, n - k); } // Driver code public static void main(String[] args) { int n = 10; int k = 5; float p = (float)1.0 / 3; float probability = binomialProbability(n, k, p); System.out.print("Probability of " +k); System.out.print(" heads when a coin is tossed " +n); System.out.println(" times where probability of each head is " +p); System.out.println( " is = " + probability ); } } /* This code is contributed by Mr. Somesh Awasthi */ Python3 # Python3 program to compute Binomial # Probability # function to calculate nCr i.e., # number of ways to choose r out # of n objects def nCr(n, r): # Since nCr is same as nC(n-r) # To decrease number of iterations if (r > n / 2): r = n - r; answer = 1; for i in range(1, r + 1): answer *= (n - r + i); answer /= i; return answer; # function to calculate binomial r.v. # probability def binomialProbability(n, k, p): return (nCr(n, k) * pow(p, k) * pow(1 - p, n - k)); # Driver code n = 10; k = 5; p = 1.0 / 3; probability = binomialProbability(n, k, p); print("Probability of", k, "heads when a coin is tossed", end = " "); print(n, "times where probability of each head is", round(p, 6)); print("is = ", round(probability, 6)); # This code is contributed by mits C# // C# program to compute Binomial // Probability. using System; class GFG { // function to calculate nCr // i.e., number of ways to // choose r out of n objects static int nCr(int n, int r) { // Since nCr is same as // nC(n-r) To decrease // number of iterations if (r > n / 2) r = n - r; int answer = 1; for (int i = 1; i <= r; i++) { answer *= (n - r + i); answer /= i; } return answer; } // function to calculate binomial // r.v. probability static float binomialProbability( int n, int k, float p) { return nCr(n, k) * (float)Math.Pow(p, k) * (float)Math.Pow(1 - p, n - k); } // Driver code public static void Main() { int n = 10; int k = 5; float p = (float)1.0 / 3; float probability = binomialProbability(n, k, p); Console.Write("Probability of " + k); Console.Write(" heads when a coin " + "is tossed " + n); Console.Write(" times where " + "probability of each head is " + p); Console.Write( " is = " + probability ); } } // This code is contributed by nitin mittal. JavaScript <script> // Javascript program to compute Binomial Probability // function to calculate nCr i.e., number of // ways to choose r out of n objects function nCr(n, r) { // Since nCr is same as nC(n-r) // To decrease number of iterations if (r > n / 2) r = n - r; let answer = 1; for (let i = 1; i <= r; i++) { answer *= (n - r + i); answer /= i; } return answer; } // function to calculate binomial r.v. probability function binomialProbability(n, k, p) { return nCr(n, k) * Math.pow(p, k) * Math.pow(1 - p, n - k); } // driver program let n = 10; let k = 5; let p = 1.0 / 3; let probability = binomialProbability(n, k, p); document.write("Probability of " +k); document.write(" heads when a coin is tossed " +n); document.write(" times where probability of each head is " +p); document.write( " is = " + probability ); // This code is contributed by code_hunt. </script> PHP <?php // php program to compute Binomial // Probability // function to calculate nCr i.e., // number of ways to choose r out // of n objects function nCr($n, $r) { // Since nCr is same as nC(n-r) // To decrease number of iterations if ($r > $n / 2) $r = $n - $r; $answer = 1; for ($i = 1; $i <= $r; $i++) { $answer *= ($n - $r + $i); $answer /= $i; } return $answer; } // function to calculate binomial r.v. // probability function binomialProbability($n, $k, $p) { return nCr($n, $k) * pow($p, $k) * pow(1 - $p, $n - $k); } // Driver code $n = 10; $k = 5; $p = 1.0 / 3; $probability = binomialProbability($n, $k, $p); echo "Probability of " . $k; echo " heads when a coin is tossed " . $n; echo " times where probability of " . "each head is " . $p ; echo " is = " . $probability ; // This code is contributed by nitin mittal. ?> Output: Probability of 5 heads when a coin is tossed 10 times where probability of each head is 0.333333 is = 0.136565 Comment More infoAdvertise with us Next Article Randomized Algorithms | Set 0 (Mathematical Background) P Pratik Chhajer Improve Article Tags : Mathematical Randomized DSA Practice Tags : Mathematical Similar Reads Randomized Algorithms Randomized algorithms in data structures and algorithms (DSA) are algorithms that use randomness in their computations to achieve a desired outcome. These algorithms introduce randomness to improve efficiency or simplify the algorithm design. By incorporating random choices into their processes, ran 2 min read Random Variable Random variable is a fundamental concept in statistics that bridges the gap between theoretical probability and real-world data. 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