Select the statistics for Column Statistics and Row Statistics

The sum is the total of all of the data values.

Use the mean to describe the sample with a single value that represents the center of the data. Many statistical analyses use the mean as a standard measure of the center of the distribution of the data.

Use the standard deviation to determine how spread out the data are from the mean. For more information, go to What is the standard deviation?

The minimum is the smallest data value in the sample. Use the minimum to identify a possible outlier or a data entry mistake. One of the simplest ways to assess the spread of your data is to compare the minimum and maximum.

The maximum is the largest data value in the sample. Use the maximum to identify a possible outlier or a data entry mistake. One of the simplest ways to assess the spread of your data is to compare the minimum and maximum.

The range is the difference between the largest and smallest data values in the sample. The range represents the smallest interval that contains all the data values.

The median is another measure of the center of the distribution of the data. The median is usually less influenced by outliers than the mean. Half the data values are greater than the median value, and half the data values are less than the median value.

The uncorrected sum of squares are calculated by squaring each value in the column, and then adding those squared values. For example, if the column contains x₁, x₂, ... , x_n, then the sum of squares is calculated as (x₁² + x₂² + ... + x_n²). Unlike the corrected sum of squares, the uncorrected sum of squares includes error. The data values are squared without first subtracting the mean.

The total number of observations in the column. Use to represent the sum of N missing and N nonmissing. Minitab displays this value in the output as Total Count.

The number of missing values in the sample. The number of missing values refers to cells that contain the missing value symbol *. Minitab displays this value in the output as N*.

The number of non-missing values in the sample. Minitab displays this value in the output as N.