How to find variance in golang

In data analysis, variance is a very basic concept. In the Go language, finding the variance is also very simple. This article will help readers understand how to find variance in Go.

1. Definition of variance

Variance is a measure of the dispersion of the data distribution. The larger the variance, the higher the dispersion of the data; conversely, the smaller the variance, the lower the dispersion of the data.

Variance formula:

$\sigma^2 = \frac{\sum_{i=1}^n (x_i - \mu)^2}{n}$

Among them, $x_i$ represents the $i$-th data, $\mu$ represents the mean of all data, and $n$ represents the number of data.

2. Implementation of finding variance

In Go, finding variance can be implemented using the following code:

package main

import (
    "fmt"
    "math"
)

func main() {
    // 原始数据
    data := []float64{1, 2, 3, 4, 5}
    
    // 求均值
    mean := mean(data)
    
    // 求方差
    variance := variance(data, mean)
    
    fmt.Println(variance)
}

// 求均值
func mean(data []float64) float64 {
    sum := 0.0

    for _, value := range data {
        sum += value
    }

    return sum / float64(len(data))
}

// 求方差
func variance(data []float64, mean float64) float64 {
    sum := 0.0

    for _, value := range data {
        sum += math.Pow(value - mean, 2)
    }

    return sum / float64(len(data))
}

First, define a slice, and then call the mean and variance functions.

The mean function is used to find the mean of the original data. Use a for loop to traverse the data to sum, and then divide by the number of data.

The variance function is used to find the variance. First use a for loop to traverse the data, then use the math.Pow function to find the square of the difference between each data and the mean, and add all the squares. Finally divide it by the number of data.

3. Realization of finding standard deviation

For variance, another very important concept is standard deviation. Standard deviation is the square root of the variance and describes how volatile the data is. The larger the standard deviation, the greater the fluctuation of the data. On the contrary, the smaller the standard deviation, the smaller the fluctuation of the data.

To find the standard deviation in Go, you can use the following code:

package main

import (
    "fmt"
    "math"
)

func main() {
    // 原始数据
    data := []float64{1, 2, 3, 4, 5}
    
    // 求均值
    mean := mean(data)
    
    // 求标准差
    stdDev := stdDev(data, mean)
    
    fmt.Println(stdDev)
}

// 求标准差
func stdDev(data []float64, mean float64) float64 {
    sum := 0.0

    for _, value := range data {
        sum += math.Pow(value - mean, 2)
    }

    variance := sum / float64(len(data))

    return math.Sqrt(variance)
}

The implementation of finding the standard deviation is very similar to finding the variance. You only need to use the math.Sqrt function at the end of the variance function to find the square root. Can.

4. Summary

This article introduces the implementation method of finding variance and standard deviation in Go. Variance and standard deviation are very important concepts for data analysis and processing. The code provided in this article is simple and easy to understand, and can help readers quickly understand and apply it. If you want to learn more about data analysis and processing, mastering the calculations of variance and standard deviation is essential.

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