查找两个系列的组合均值和方差

给定大小为n和m的两个不同的序列arr1 [n]和arr2 [m] 。任务是找到组合级数的均值和方差。

例子 ：

Input : arr1[] = {3, 5, 1, 7, 8, 5}
        arr2[] = {5, 9, 7, 1, 5, 4, 7, 3}
Output : Mean1: 4.83333   mean2: 5.125
         StandardDeviation1: 5.47222   
         StandardDeviation2: 5.60938
         Combined Mean: 5
         d1_square: 0.0277777  
         d2_square: 0.015625
         Combined Variance: 5.57143

Input : arr1[] = {23, 45, 34, 78, 12, 76, 34}
        arr2[] = {65, 67, 34, 23, 45}
Output : Mean1: 43.1429   mean2: 46.8
         StandardDeviation1: 548.694   
         StandardDeviation2: 294.56
         Combined Mean: 44.6667
         d1_square: 2.32199  
         d2_square: 4.55112
         Combined Variance: 446.056

方法：
方差$\alpha ^{2}$组合系列的
$\alpha ^{2} = \frac{1}{n_{1} + n_{2}}\left [ n_{1} \left ( \alpha _{1}^{2} + d_{1}^{2} \right ) + n_{2} \left ( \alpha _{2}^{2} + d_{2}^{2} \right ) \right ]$
在哪里$d_{1} = \bar{x_{1}} - \bar{x}$ ， $d_{2} = \bar{x_{2}} - \bar{x}$
和$\bar{x} = \frac{n_{1} \bar{x_{1}} + n_{2} \bar{x_{2}}}{n_{1} + n_{2}}$ ，是合并级数的均值。
$\sigma _{1}^{2} = \frac{1}{n_{1}} \sum_{i = 1}^{n_{1}}\left ( x_{1i} - \bar{x_{1}} \right )^{2}$
$\sigma _{2}^{2} = \frac{1}{n_{2}} \sum_{j = 1}^{n_{2}}\left ( x_{2j} - \bar{x_{2}} \right )^{2}$
$\bar{x_{1}}$ ， $\bar{x_{2}}$是手段和$\sigma _{1}$ ， $\sigma _{2}$是两个系列的标准偏差。
$\bar{x_{1}} = \frac{1}{n_{1}} \sum_{i = 1}^{n_{1}}x_{1i}$
$\bar{x_{2}} = \frac{1}{n_{2}} \sum_{j = 1}^{n_{2}}x_{2j}$

下面是上述公式的实现：

C++

// C++ program to find combined mean
// and variance of two series.
#include 
using namespace std;
  
// Function to find mean of series.
float mean(int arr[], int n)
{
    int sum = 0;
    for (int i = 0; i < n; i++)
        sum = sum + arr[i];
      
    float mean = (float)sum / n;
    return mean;
}
  
// Function to find the standard 
// deviation of series.
float sd(int arr[], int n)
{
    float sum = 0;
    for (int i = 0; i < n; i++)
        sum = sum + (arr[i] - mean(arr, n)) *
              (arr[i] - mean(arr, n));
      
    float sdd = sum / n;
    return sdd;
}
  
// Function to find combined variance
// of two different series.
float combinedVariance(int arr1[], int arr2[],
                                int n, int m)
{
    // mean1 and mean2 are the mean 
    // of two arrays.
    float mean1 = mean(arr1, n);
    float mean2 = mean(arr2, m);
      
    cout << "Mean1: " << mean1 
         << " mean2: " << mean2 << endl;
  
    // sd1 and sd2 are the standard 
    // deviation of two array.
    float sd1 = sd(arr1, n);
    float sd2 = sd(arr2, m);
      
    cout << "StandardDeviation1: " << sd1 
         << " StandardDeviation2: " << sd2
         << endl;
  
    // combinedMean is variable to store
    // the combined mean of both array.
    float combinedMean = (float)(n * mean1 +
                         m * mean2) / (n + m);
      
    cout << "Combined Mean: " << combinedMean 
         << endl;
  
    // d1_square and d2_square are 
    // the combined mean deviation.
    float d1_square = (mean1 - combinedMean) *
                      (mean1 - combinedMean);
    float d2_square = (mean2 - combinedMean) * 
                      (mean2 - combinedMean);
      
    cout << "d1 square: " << d1_square 
         << " d2_square: " << d2_square 
         << endl;
  
    // combinedVar is variable to store 
    // combined variance of both array.
    float combinedVar = (n * (sd1 + d1_square) + m *
                       (sd2 + d2_square)) / (n + m);
    return combinedVar;
}
  
// Driver function.
int main()
{
    int arr1[] = { 23, 45, 34, 78, 12, 76, 34 };
    int arr2[] = { 65, 67, 34, 23, 45 };
    int n = sizeof(arr1) / sizeof(arr1[0]);
    int m = sizeof(arr2) / sizeof(arr2[0]);
      
    // Function call to combined mean.
    cout << "Combined Variance: " 
         << combinedVariance(arr1, arr2, n, m);
    return 0;
}

Java

// Java program to find combined mean
// and variance of two series.
  
import java.io.*;
  
class GFG {
      
    // Function to find mean of series.
    static float mean(int arr[], int n)
    {
        int sum = 0;
          
        for (int i = 0; i < n; i++)
            sum = sum + arr[i];
          
        float mean = (float)sum / n;
          
        return mean;
    }
      
    // Function to find the standard 
    // deviation of series.
    static float sd(int arr[], int n)
    {
        float sum = 0;
        for (int i = 0; i < n; i++)
            sum = sum + (arr[i] - mean(arr, n)) *
                            (arr[i] - mean(arr, n));
          
        float sdd = sum / n;
          
        return sdd;
    }
      
    // Function to find combined variance
    // of two different series.
    static float combinedVariance(int arr1[],
                        int arr2[], int n, int m)
    {
        // mean1 and mean2 are the mean 
        // of two arrays.
        float mean1 = mean(arr1, n);
        float mean2 = mean(arr2, m);
          
        System.out.print("Mean1: " + mean1 + " ") ;
        System.out.println("Mean2: " + mean2) ;
      
        // sd1 and sd2 are the standard 
        // deviation of two array.
        float sd1 = sd(arr1, n);
        float sd2 = sd(arr2, m);
          
        System.out.print("StandardDeviation1: " 
                                   + sd1 + " ") ;
                                     
        System.out.println("StandardDeviation2: "
                                    + sd2 + " ");
      
      
        // combinedMean is variable to store
        // the combined mean of both array.
        float combinedMean = (float)(n * mean1 +
                                m * mean2) / (n + m);
          
        System.out.println( "Combined Mean: "
                            + combinedMean + " "); 
              
      
        // d1_square and d2_square are 
        // the combined mean deviation.
        float d1_square = (mean1 - combinedMean) *
                            (mean1 - combinedMean);
          
        float d2_square = (mean2 - combinedMean) * 
                            (mean2 - combinedMean);
          
        System.out.print("d1 square: " + d1_square + " " ); 
        System.out.println("d2_square: " + d2_square); 
      
        // combinedVar is variable to store 
        // combined variance of both array.
        float combinedVar = (n * (sd1 + d1_square)
                    + m * (sd2 + d2_square)) / (n + m);
          
        return combinedVar;
    }
      
       // Driver function.
        public static void main (String[] args) {
          
        int arr1[] = { 23, 45, 34, 78, 12, 76, 34 };
        int arr2[] = { 65, 67, 34, 23, 45 };
        int n = arr1.length;
        int m = arr2.length;
          
        // Function call to combined mean.
            System.out.println("Combined Variance: "
                + combinedVariance(arr1, arr2, n, m));
        }
}
  
  
// This code is contributed by vt_m.

Python3

# Python3 program to find 
# combined mean and variance
# of two series.
  
# Function to find
# mean of series.
def mean(arr, n):
    sum = 0;
    for i in range(n):
        sum = sum + arr[i];
    mean = sum / n;
    return mean;
  
# Function to find the 
# standard deviation 
# of series.
def sd(arr, n):
    sum = 0;
    for i in range(n):
        sum = sum + ((arr[i] - mean(arr, n)) * 
                     (arr[i] - mean(arr, n)));
    sdd = sum / n;
    return sdd;
  
# Function to find combined 
# variance of two different
# series.
def combinedVariance(arr1, arr2, n, m):
      
    # mean1 and mean2 are 
    # the mean of two arrays.
    mean1 = mean(arr1, n);
    mean2 = mean(arr2, m);
      
    print("Mean1: ", round(mean1, 2), 
          " mean2: ", round(mean2, 2));
  
    # sd1 and sd2 are the standard
    # deviation of two array.
    sd1 = sd(arr1, n);
    sd2 = sd(arr2, m);
      
    print("StandardDeviation1: ", round(sd1, 2), 
          " StandardDeviation2: ", round(sd2, 2));
      
    # combinedMean is variable 
    # to store the combined 
    # mean of both array.
    combinedMean = (n * mean1 + 
                    m * mean2) / (n + m);
    print("Combined Mean: ", 
           round(combinedMean, 2));
      
    # d1_square and d2_square are
    # the combined mean deviation.
    d1_square = ((mean1 - combinedMean) * 
                 (mean1 - combinedMean));
    d2_square = ((mean2 - combinedMean) * 
                 (mean2 - combinedMean));
    print("d1 square: ", round(d1_square, 2),
          " d2_square: ", round(d2_square, 2));
      
    # combinedVar is variable to 
    # store combined variance of 
    # both array.
    combinedVar = (n * (sd1 + d1_square) + 
                   m * (sd2 + d2_square)) / (n + m);
    print("Combined Variance: ", 
         round(combinedVar, 2));
  
# Driver Code
arr1 = [ 23, 45, 34, 78, 12, 76, 34 ];
arr2 = [ 65, 67, 34, 23, 45 ];
n = len(arr1);
m = len(arr2);
      
# Function call to combined mean.
combinedVariance(arr1, arr2, n ,m);
  
# This code is contributed by mits

C#

// C# program to find combined mean
// and variance of two series.
using System;
  
class GFG {
      
    // Function to find mean of series.
    static float mean(int []arr, int n)
    {
        int sum = 0;
          
        for (int i = 0; i < n; i++)
            sum = sum + arr[i];
          
        float mean = (float)sum / n;
          
        return mean;
    }
      
    // Function to find the standard 
    // deviation of series.
    static float sd(int []arr, int n)
    {
        float sum = 0;
        for (int i = 0; i < n; i++)
            sum = sum + (arr[i] - mean(arr, n)) *
                        (arr[i] - mean(arr, n));
          
        float sdd = sum / n;
        return sdd;
    }
      
    // Function to find combined variance
    // of two different series.
    static float combinedVariance(int []arr1,
                                     int []arr2, 
                                     int n, int m)
    {
          
        // mean1 and mean2 are the 
        // mean of two arrays.
        float mean1 = mean(arr1, n);
        float mean2 = mean(arr2, m);
          
        Console.Write("Mean1: " + mean1 + " ") ;
        Console.WriteLine("Mean2: " + mean2) ;
      
        // sd1 and sd2 are the standard 
        // deviation of two array.
        float sd1 = sd(arr1, n);
        float sd2 = sd(arr2, m);
          
        Console.Write("StandardDeviation1: "
                                + sd1 + " ") ;
                                      
        Console.WriteLine("StandardDeviation2: "
                                + sd2 + " ");
      
      
        // combinedMean is variable to store
        // the combined mean of both array.
        float combinedMean = (float)(n * mean1 +
                              m * mean2) / (n + m);
          
        Console.WriteLine("Combined Mean: "
                           + combinedMean + " "); 
              
      
        // d1_square and d2_square are 
        // the combined mean deviation.
        float d1_square = (mean1 - combinedMean) *
                             (mean1 - combinedMean);
          
        float d2_square = (mean2 - combinedMean) * 
                          (mean2 - combinedMean);
          
        Console.Write("d1 square: " + 
                       d1_square + " " ); 
        Console.WriteLine("d2_square: " + 
                           d2_square); 
      
        // combinedVar is variable to store 
        // combined variance of both array.
        float combinedVar = (n * (sd1 + d1_square)    +
                             m * (sd2 + d2_square)) /
                            (n + m);
          
        return combinedVar;
    }
      
// Driver code
public static void Main ()
{
        int []arr1 = {23, 45, 34, 78, 12, 76, 34};
        int []arr2 = {65, 67, 34, 23, 45};
        int n = arr1.Length;
        int m = arr2.Length;
          
        // Function call to combined mean.
        Console.WriteLine("Combined Variance: " + 
                           combinedVariance(arr1, arr2,
                           n, m));
        }
}
  
// This code is contributed by vt_m.

输出 ：

Mean1: 43.1429 mean2: 46.8
StandardDeviation1: 548.694 StandardDeviation2: 294.56
Combined Mean: 44.6667
d1 square: 2.322 d2_square: 4.5511
Combined Variance: 446.056