Standard deviation of a number

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Standard deviation of a number
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Standard deviation is an indicator to measure the dispersion of data sets, which can be obtained by calculating the arithmetic square root of variance. The standard deviation represents the distance between each data point and the average value, which can reflect the dispersion degree of the data set.
The calculation of standard deviation usually goes through the following four steps:
1. Calculate the average value: add all data points and divide by the number of samples to get the average value.
2. Calculate variance: accumulate the square of the difference between each number and the average, and then divide the cumulative result by the number of samples to get the variance.
3. Calculate the average variance: divide the variance by the number of samples to get the average variance.
4. Calculate the standard deviation: calculate the square root of the average variance to obtain the standard deviation of the sample.
The following is an example to illustrate how to calculate the standard deviation of a set with six numbers (2,3,4,5,6,8):
First calculate the average value of the set:
(2 + 3 + 4 + 5+ 6 + 8)/6 = 30 /6 = 5
Then calculate the square of the difference between each number and the average, and add them to get the variance:
(2 – 5)^2 = (-3)^2= 9
(3 – 5)^2 = (-2)^2= 4
(4 – 5)^2 = (-1)^2= 0
(5 – 5)^2 = 0^2= 0
(6 – 5)^2 = 1^2= 1
(8 – 5)^2 = 3^2= 9
Then divide the variance by the number of samples to get the average variance:
24/6 = 4
Finally, the standard deviation of the sample is obtained by calculating the square root of the mean variance:
√4 = 2
Therefore, the standard deviation of the set with six numbers is 2.
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Manually delete the maximum and minimum values after sorting in Excel;
Or use VBA programming to achieve.
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Both upstairs are strong men, both right
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method:
1. After opening the EXCEL table, for example, calculate the percentage increase of column B1 compared with column A1.
2. Enter=(B1-A1)/A1 in column C1, and then set the cell as a percentage style.
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Multiply the original data by (*) 0.8
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