The classical statistical analysis of the data described in this paper includes calculating the extreme value, average value, median value, standard deviation, variance, coefficient of variation, skewness and kurtosis of the data.

First, open the SPSS software.

The first step is to import the data into SPSS. Select file, and then select data.

Select the data format to be imported in the pop-up window, then select the data path and data file, and finally click "Open". The data used in this article are found in. Csv format, so the file type is selected as CSV(*. csv)。

Then enter the text import wizard window. It needs to be configured according to the actual situation of imported data.

For example, the first line of. The csv data used in this paper is the column name, so the variable name line in the following figure is 1 line.

Therefore, the line at the beginning of the data case is the second line.

When all the configurations are completed, click Finish. At this point, all the data have been imported into SPSS.

Then, select Analysis, and in Compare Average, select Average.

First, put the variables that need to calculate statistical indicators into the dependent variable list.

Then, select "Options" and put the items to be calculated in the "Cell Statistics" column.

Click Continue, and then click OK. The results will be displayed in the output document.

In addition, the calculation of statistical indicators can also be achieved by selecting description → description statistics from the analysis.

The results are as follows:

Finally, it should be noted that at present, SPSS cannot directly calculate the coefficient of variation. We can directly calculate the coefficient of variation after calculating the standard deviation and average value of the data by the above method: the coefficient of variation is equal to the standard deviation divided by the average value.