How many people must be there in a room to make the probability 100% that at-least two people in the room have same birthday?
Answer: 367 (since there are 366 possible birthdays, including February 29).
The above question was simple. Try the below question yourself.
How many people must be there in a room to make the probability 50% that at-least two people in the room have same birthday?
Answer: 23
The number is surprisingly very low. In fact, we need only 70 people to make the probability 99.9 %.
Let us discuss the generalized formula.
What is the probability that two persons among n have same birthday?
Let the probability that two people in a room with n have same birthday be P(same). P(Same) can be easily evaluated in terms of P(different) where P(different) is the probability that all of them have different birthday.
P(same) = 1 - P(different)
P(different) can be written as 1 x (364/365) x (363/365) x (362/365) x .... x (1 - (n-1)/365)
How did we get the above expression?
Persons from first to last can get birthdays in following order for all birthdays to be distinct:
The first person can have any birthday among 365
The second person should have a birthday which is not same as first person
The third person should have a birthday which is not same as first two persons.
................
...............
The n'th person should have a birthday which is not same as any of the earlier considered (n-1) persons.
Approximation of above expression
The above expression can be approximated using Taylor's Series.
e^{x}=1+x+\frac{x^{2}}{2!}+...
provides a first-order approximation for ex for x << 1:
e^{x}\approx 1+x
To apply this approximation to the first expression derived for p(different), set x = -a / 365. Thus,
\Large{e^{\frac{-a}{365}}\approx 1-\frac {a}{365}}
The above expression derived for p(different) can be written as
1 x (1 - 1/365) x (1 - 2/365) x (1 - 3/365) x …. x (1 – (n-1)/365)
By putting the value of 1 - a/365 as e-a/365, we get following.
\approx 1\times e^{\frac{-1}{365}}\times e^{\frac{-2}{365}}...\times e^{\frac{-(n-1)}{365}}
\approx 1\times e^{\frac{-(1+2+...+(n-1))}{365}}
\approx 1\times e^{\frac {-(n(n-1))/2}{365}}
Therefore,
p(same) = 1- p(different)
\approx 1-e^{-n(n-1)/(2 \times 365)}
An even coarser approximation is given by
p(same)
\approx 1-e^{-n^{2}/(2 \times 365)}
By taking Log on both sides, we get the reverse formula.
n \approx \sqrt{2 \times 365 ln\left ( \frac{1}{1-p(same)} \right )}
Using the above approximate formula, we can approximate number of people for a given probability. For example the following C++ function find() returns the smallest n for which the probability is greater than the given p.
Implementation of approximate formula.
The following is program to approximate number of people for a given probability.
C++
// C++ program to approximate number of people in Birthday Paradox
// problem
#include <cmath>
#include <iostream>
using namespace std;
// Returns approximate number of people for a given probability
int find(double p)
{
return ceil(sqrt(2*365*log(1/(1-p))));
}
int main()
{
cout << find(0.70);
}
Java
// Java program to approximate number
// of people in Birthday Paradox problem
class GFG {
// Returns approximate number of people
// for a given probability
static double find(double p) {
return Math.ceil(Math.sqrt(2 *
365 * Math.log(1 / (1 - p))));
}
// Driver code
public static void main(String[] args)
{
System.out.println(find(0.70));
}
}
// This code is contributed by Anant Agarwal.
Python3
# Python3 code to approximate number
# of people in Birthday Paradox problem
import math
# Returns approximate number of
# people for a given probability
def find( p ):
return math.ceil(math.sqrt(2 * 365 *
math.log(1/(1-p))));
# Driver Code
print(find(0.70))
# This code is contributed by "Sharad_Bhardwaj".
C#
// C# program to approximate number
// of people in Birthday Paradox problem.
using System;
class GFG {
// Returns approximate number of people
// for a given probability
static double find(double p) {
return Math.Ceiling(Math.Sqrt(2 *
365 * Math.Log(1 / (1 - p))));
}
// Driver code
public static void Main()
{
Console.Write(find(0.70));
}
}
// This code is contributed by nitin mittal.
PHP
<?php
// PHP program to approximate
// number of people in Birthday
// Paradox problem
// Returns approximate number
// of people for a given probability
function find( $p)
{
return ceil(sqrt(2 * 365 *
log(1 / (1 - $p))));
}
// Driver Code
echo find(0.70);
// This code is contributed by aj_36
?>
JavaScript
<script>
// JavaScript program to approximate number
// of people in Birthday Paradox problem
// Returns approximate number of
// people for a given probability
function find( p){
return Math.ceil(Math.sqrt(2*365*Math.log(1/(1-p))));
}
document.write(find(0.70));
</script>
Time Complexity: O(log n)
Auxiliary Space: O(1)
Source:
https://en.wikipedia.org/wiki/Birthday_problem
Applications:
1) Birthday Paradox is generally discussed with hashing to show importance of collision handling even for a small set of keys.
2) Birthday Attack
Below is an implementation:
C
#include<stdio.h>
int main(){
// Assuming non-leap year
float num = 365;
float denom = 365;
float pr;
int n = 0;
printf("Probability to find : ");
scanf("%f", &pr);
float p = 1;
while (p > pr){
p *= (num/denom);
num--;
n++;
}
printf("\nTotal no. of people out of which there "
" is %0.1f probability that two of them "
"have same birthdays is %d ", p, n);
return 0;
}
C++
// CPP program for the above approach
#include <bits/stdc++.h>
using namespace std;
int main(){
// Assuming non-leap year
float num = 365;
float denom = 365;
float pr;
int n = 0;
cout << "Probability to find : " << endl;
cin >> pr;
float p = 1;
while (p > pr){
p *= (num/denom);
num--;
n++;
}
cout << " Total no. of people out of which there is " << p
<< "probability that two of them have same birthdays is " << n << endl;
return 0;
}
// This code is contributed by sanjoy_62.
Java
class GFG{
public static void main(String[] args){
// Assuming non-leap year
float num = 365;
float denom = 365;
double pr=0.7;
int n = 0;
float p = 1;
while (p > pr){
p *= (num/denom);
num--;
n++;
}
System.out.printf("\nTotal no. of people out of which there is ");
System.out.printf( "%.1f probability that two of them "
+ "have same birthdays is %d ", p, n);
}
}
// This code is contributed by Rajput-Ji
Python3
if __name__ == '__main__':
# Assuming non-leap year
num = 365;
denom = 365;
pr = 0.7;
n = 0;
p = 1;
while (p > pr):
p *= (num / denom);
num -= 1;
n += 1;
print("Total no. of people out of which there is ", end="");
print ("{0:.1f}".format(p), end="")
print(" probability that two of them " + "have same birthdays is ", n);
# This code is contributed by Rajput-Ji
C#
using System;
public class GFG {
public static void Main(String[] args) {
// Assuming non-leap year
float num = 365;
float denom = 365;
double pr = 0.7;
int n = 0;
float p = 1;
while (p > pr) {
p *= (num / denom);
num--;
n++;
}
Console.Write("\nTotal no. of people out of which there is ");
Console.Write("{0:F1} probability that two of them have same birthdays is {1} ", p, n);
}
}
// This code is contributed by Rajput-Ji
JavaScript
<script>
// Assuming non-leap year
var num = 365;
var denom = 365;
var pr = 0.7;
var n = 0;
var p = 1;
while (p > pr) {
p *= (num / denom);
num--;
n++;
}
document.write("\nTotal no. of people out of which there is ");
document.write(p.toFixed(1)+" probability that two of them " + "have same birthdays is "+ n);
// This code is contributed by Rajput-Ji
</script>
OutputProbability to find :
Total no. of people out of which there is 0.0 probability that two of them have same birthdays is 239
Time Complexity: O(log n)
Auxiliary Space: O(1)
Similar Reads
Basics & Prerequisites
Data Structures
Array Data StructureIn this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
3 min read
String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut
2 min read
Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The
2 min read
Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Hereâs the comparison of Linked List vs Arrays Linked List:
2 min read
Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first
2 min read
Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems
2 min read
Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most
4 min read
Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of
3 min read
Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this
15+ min read
Algorithms
Searching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input
2 min read
Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read
Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution
14 min read
Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get
3 min read
Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net
3 min read
Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit
4 min read
Advanced
Segment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree
3 min read
Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i
2 min read
GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br
2 min read
Interview Preparation
Practice Problem