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Probability such that two subset contains same number of elements

Given a set containing N elements. If two subset X and Y picked then find the probability that both of them contains the same number of elements.
Examples: 
 

Input:
Output: 35/128 
Input:
Output: 3/8 
 


 


Approach: 
Let’s choose a subset X that has r number of elements then Y must contain r number of elements. A subset can have minimum 0 elements and maximum N elements.
Total number of subsets of a set contains N number of elements is 

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, Total possible way to choose X and Y simultaneously will be 
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*** QuickLaTeX cannot compile formula:
 

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*** Error message:
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.
Let, P = Total possible way to choose X and Y such that both have the same number of elements.
Then P = 
So the required probability will be .
Below is the implementation of the above Approach:
 
// C++ implementation of
// the above approach
#include <bits/stdc++.h>
using namespace std;
 
// Returns value of Binomial
// Coefficient C(n, k)
int binomialCoeff(int n, int k)
{
    int res = 1;
 
    // Since C(n, k) = C(n, n-k)
    if (k > n - k)
        k = n - k;
 
    // Calculate value of
    for (int i = 0; i < k; ++i) {
        res *= (n - i);
        res /= (i + 1);
    }
 
    return res;
}
 
// Iterative Function to
// calculate (x^y) in O(log y)
int power(int x, unsigned int y)
{
    // Initialize result
    int res = 1;
 
    while (y > 0) {
 
        // If y is odd, multiply
        // x with result
        if (y & 1)
            res = res * x;
 
        // y must be even now
        // y = y/2
        y = y >> 1;
 
        // Change x to x^2
        x = x * x;
    }
    return res;
}
 
// Function to find probability
void FindProbability(int n)
{
 
    // Calculate total possible
    // ways and favourable ways.
    int up = binomialCoeff(2 * n, n);
    int down = power(2, 2 * n);
 
    // Divide by gcd such that
    // they become relatively coprime
    int g = __gcd(up, down);
 
    up /= g, down /= g;
 
    cout << up << "/" << down << endl;
}
 
// Driver code
int main()
{
 
    int N = 8;
 
    FindProbability(N);
 
    return 0;
}

                    
// Java implementation of
// the above approach
class GFG
{
     
    // Returns value of Binomial
    // Coefficient C(n, k)
    static int binomialCoeff(int n, int k)
    {
        int res = 1;
     
        // Since C(n, k) = C(n, n-k)
        if (k > n - k)
            k = n - k;
     
        // Calculate value of
        for (int i = 0; i < k; ++i)
        {
            res *= (n - i);
            res /= (i + 1);
        }
     
        return res;
    }
     
    // Iterative Function to
    // calculate (x^y) in O(log y)
    static int power(int x, int y)
    {
        // Initialize result
        int res = 1;
     
        while (y > 0)
        {
     
            // If y is odd, multiply
            // x with result
            if ((y & 1) == 1)
                res = res * x;
     
            // y must be even now
            // y = y/2
            y = y >> 1;
     
            // Change x to x^2
            x = x * x;
        }
        return res;
    }
     
    // Recursive function to return gcd of a and b
    static int gcd(int a, int b)
    {
        if (b == 0)
            return a;
        return gcd(b, a % b);
         
    }
     
    // Function to find probability
    static void FindProbability(int n)
    {
     
        // Calculate total possible
        // ways and favourable ways.
        int up = binomialCoeff(2 * n, n);
        int down = power(2, 2 * n);
     
        // Divide by gcd such that
        // they become relatively coprime
        int g = gcd(up, down);
     
        up /= g;
        down /= g;
     
        System.out.println(up + "/" + down);
    }
     
    // Driver code
    public static void main (String[] args)
    {
        int N = 8;
     
        FindProbability(N);
    }
}
 
// This code is contributed by AnkitRai01

                    
# Python3 implementation of
# the above approach
import math
 
# Returns value of Binomial
# Coefficient C(n, k)
def binomialCoeff(n, k):
 
    res = 1
 
    # Since C(n, k) = C(n, n-k)
    if (k > n - k):
        k = n - k
 
    # Calculate value of
    for i in range(0, k):
        res = res * (n - i)
        res = res // (i + 1)
 
    return res
 
# Iterative Function to
# calculate (x^y) in O(log y)
def power(x, y):
     
    # Initialize result
    res = 1
 
    while (y > 0):
 
        # If y is odd, multiply
        # x with result
        if (y & 1):
            res = res * x
 
        # y must be even now
        # y = y/2
        y = y // 2
 
        # Change x to x^2
        x = x * x
     
    return res
 
# Function to find probability
def FindProbability(n):
 
    # Calculate total possible
    # ways and favourable ways.
    up = binomialCoeff(2 * n, n)
    down = power(2, 2 * n)
 
    # Divide by gcd such that
    # they become relatively coprime
    g = math.gcd(up,down)
 
    up = up // g
    down = down // g
 
    print(up, "/", down)
 
# Driver code
N = 8
FindProbability(N)
 
# This code is contributed by Sanjit_Prasad

                    
// C# implementation of
// the above approach
using System;
using System.Collections.Generic;
     
class GFG
{
     
    // Returns value of Binomial
    // Coefficient C(n, k)
    static int binomialCoeff(int n, int k)
    {
        int res = 1;
     
        // Since C(n, k) = C(n, n-k)
        if (k > n - k)
            k = n - k;
     
        // Calculate value of
        for (int i = 0; i < k; ++i)
        {
            res *= (n - i);
            res /= (i + 1);
        }
     
        return res;
    }
     
    // Iterative Function to
    // calculate (x^y) in O(log y)
    static int power(int x, int y)
    {
        // Initialize result
        int res = 1;
     
        while (y > 0)
        {
     
            // If y is odd, multiply
            // x with result
            if ((y & 1) == 1)
                res = res * x;
     
            // y must be even now
            // y = y/2
            y = y >> 1;
     
            // Change x to x^2
            x = x * x;
        }
        return res;
    }
     
    // Recursive function to
    // return gcd of a and b
    static int gcd(int a, int b)
    {
        if (b == 0)
            return a;
        return gcd(b, a % b);
    }
     
    // Function to find probability
    static void FindProbability(int n)
    {
     
        // Calculate total possible
        // ways and favourable ways.
        int up = binomialCoeff(2 * n, n);
        int down = power(2, 2 * n);
     
        // Divide by gcd such that
        // they become relatively coprime
        int g = gcd(up, down);
     
        up /= g;
        down /= g;
     
        Console.WriteLine(up + "/" + down);
    }
     
    // Driver code
    public static void Main (String[] args)
    {
        int N = 8;
     
        FindProbability(N);
    }
}
 
// This code is contributed by 29AjayKumar

                    
<script>
 
// Javascript implementation of
// the above approach
 
// Returns value of Binomial
// Coefficient C(n, k)
function binomialCoeff(n, k)
{
    let res = 1;
 
    // Since C(n, k) = C(n, n-k)
    if (k > n - k)
        k = n - k;
 
    // Calculate value of
    for (let i = 0; i < k; ++i) {
        res *= (n - i);
        res = parseInt(res / (i + 1));
    }
 
    return res;
}
 
// Iterative Function to
// calculate (x^y) in O(log y)
function power(x, y)
{
    // Initialize result
    let res = 1;
 
    while (y > 0) {
 
        // If y is odd, multiply
        // x with result
        if (y & 1)
            res = res * x;
 
        // y must be even now
        // y = y/2
        y = y >> 1;
 
        // Change x to x^2
        x = x * x;
    }
    return res;
}
 
// Recursive function to
// return gcd of a and b
function gcd(a, b)
{
    if (b == 0)
        return a;
    return gcd(b, a % b);
}
     
// Function to find probability
function FindProbability(n)
{
 
    // Calculate total possible
    // ways and favourable ways.
    let up = binomialCoeff(2 * n, n);
    let down = power(2, 2 * n);
 
    // Divide by gcd such that
    // they become relatively coprime
    let g = gcd(up, down);
 
    up = parseInt(up / g), down = parseInt(down / g);
 
    document.write(up + "/" + down + "<br>");
}
 
// Driver code
 
    let N = 8;
 
    FindProbability(N);
 
</script>

                    

Output: 
6435/32768

 

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