Use Excel to Do data description--Descriptive statistics

After a class midterm exam, the average and interval of statistical results are needed, as well as the quantitative standard for the difference of students ' scores in the class. We used Excel to finish the work.

After the mid-term examination of a class, the average and interval of statistical results are needed, as well as the quantitative criteria for the difference of students ' scores in the class, which can be used as the basis for solving the uneven results between classes and classes. Standard poor statistical values are required.

The sample data range and standard difference are the statistics that describe the scope and fluctuation of sample data, the statistical standard deviation needs to get the sample mean value, and the calculation is more complicated. These are common variables that describe the sample data, and can be completed once using the "descriptive statistics" in Excel data analysis.

Note: This feature requires Excel extensions, and if your Excel does not have data analysis installed, select Tools-add-ins to load the analysis database on the installation CD. After successful loading, you can see the data analysis option in the Tools Drop-down menu.

　　Operation Steps

1. Open the original data table, make the original data of this example no special requirements, as long as the row or column to meet the same attribute value.

2. Select "Tools"-"Data Analysis"-"descriptive statistics", the Property settings box appears, followed by the following:

Input range: The original data region, you can select more than one row or column, pay attention to select the appropriate grouping method;

If the data is marked, notice that the "flag is on the first line"; If the input area has no flags, the check box will be cleared and Excel will generate the appropriate data marker in the output table;

The output area can select this table, new worksheet, or new workbook;

Summary statistics: including average, standard error (relative to average), median, public number, standard deviation, Variance, peak, skewness, extreme difference, minimum, maximum, sum, total number, maximum, minimum value and confidence degree and other related items.

which

Median value: The value of the data in the middle after sorting;

Number of occurrences: the most frequent values;

Peak value: The index that measures the fluctuation of data distribution, which is based on normal distribution, is more positive than its smooth duration, whereas negative;

Skewness: An exponent that measures the peak offset of a data, either positive or negative on the left or right side of the average value;

Extreme difference: The difference between the maximum and the minimum value.

K Large (small) value: A row in the output table contains the maximum (small) value of k in each data region.

Average confidence Degree: The value 95% can be used to calculate the average confidence level at a significant 5%.

Computer Tutorials

Examples of the results are as follows (this example illustrates the descriptive statistics for two-column data):

　　Results

Study time

Average

78.64285714

Average

62.91428571

Standard error

2.408241878

Standard error

1.926593502

Median number

85

Median number

68

Public numbers

98

Public numbers

78.4

Standard deviation

18.02163202

Standard deviation

14.41730562

Variance

324.7792208

Variance

207.8587013

Peak degree

1.464424408

Peak degree

1.464424408

Degree of bias

-1.130551511

Degree of bias

-1.13055151

Regional

85

Regional

68

Minimum value

15

Minimum value

12

Maximum Value

100

Maximum Value

80

Sum

4404

Sum

3523.2

Number of observations

56

Number of observations

56

Max (1)

100

Max (1)

80

MIN (1)

15

MIN (1)

12

Confidence degree (95%)

4.826224539

Confidence degree (95%)

3.860979631