# Select the statistics for Store Column Statistics

On the Statistics tab of the Store Column Statistics dialog box, select the statistics to store.

## Mean

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.

## SE of mean

Use the standard error of the mean to determine how precisely the mean of the sample estimates the population mean.

## Standard deviation

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?.

## Variance

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

## Coefficient of variation

The coefficient of variation (denoted as COV) is a measure of spread that describes the variation in the data relative to the mean. The coefficient of variation is adjusted so that the values are on a unitless scale. Because of this adjustment, you can use the coefficient of variation instead of the standard deviation to compare the variation in data that have different units or that have very different means.

## Range

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.

## Skewness

Use skewness to determine the extent to which the data are not symmetrical. For more information, go to How skewness and kurtosis affect your distribution.

## Kurtosis

Use kurtosis to determine the extent to which the data are peaked, compared to a normal curve. For more information, go to How skewness and kurtosis affect your distribution.

## Minimum

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.

## First quartile

25% of the data values in the sample are less than the first quartile value.

## Median

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.

## Third quartile

25% of the data values in the sample are greater than the third quartile value.

## 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.

## Interquartile range

The interquartile range (IQR) is the distance between the first quartile (Q1) and the third quartile (Q3). Use the interquartile range to describe the spread of the data. As the spread of the data increases, the IQR becomes larger.

## Sum

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

## N

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

## N missing

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*.

## N total

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.

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