You can use **proc summary** in SAS to quickly calculate the following descriptive statistics for one or more variables in a dataset:

**N**: The total number of observations**MIN**: The minimum value**MAX**: The maximum value**MEAN**: The mean**STD**: The standard deviation

The following examples show how to use this procedure with the SAS built-in dataset called Fish, which contains various measurements for 159 different fish caught in a lake in Finland.

We can use **proc print** to view the first 10 observations from this dataset:

/*view first 10 observations fromFishdataset*/ proc print data=sashelp.Fish (obs=10); run;

**Related:** How to Identify Outliers in SAS

**Example 1: Proc Summary with One Variable**

We can use the following code to calculate descriptive statistics for the Weight variable:

**/*calculate descriptive statistics for Weight variable*/
proc summary data=sashelp.Fish;
var Weight;
output out=summaryWeight;
run;
/*print output dataset*/
proc print data=summaryWeight;**

Here’s how to interpret the output table:

- _TYPE_: This column shows whether or not every row in the dataset was used to calculate the descriptive statistics. 0 = Every row was used.
- _FREQ_: The number of rows used to calculate each descriptive statistic.
- _STAT_: The name of the descriptive statistic.
- Weight: The numerical value for the corresponding descriptive statistic.

From the output we can see:

- The total number of observations was
**158**. - The minimum weight value was
**0**. - The maximum weight value was
**1,650**. - The mean weight value was
**398.70**. - The standard deviation of weight values was
**359.09**.

From these five values we can gain a pretty good understanding of the distribution of values for the Weight variable.

**Example 2: Proc Summary with Multiple Variables**

To calculate descriptive statistics for multiple variables at once, simply list several variable names in the **var** statement.

For example, we can use the following code to calculate descriptive statistics for the Weight and Height variables:

**/*calculate descriptive statistics for Weight and Height variables*/
proc summary data=sashelp.Fish;
var Weight Height;
output out=summaryWeightHeight;
run;
/*print output dataset*/
proc print data=summaryWeightHeight;**

From the output we can see the five descriptive statistics for both Weight and Height.

**Example 3: Proc Summary with One Variable Grouped by Another Variable**

To calculate descriptive statistics for one variable grouped by another variable, we can use the **class** statement.

For example, we can use the following code to calculate descriptive statistics for Weight grouped by Species:

**/*calculate descriptive statistics for Weight grouped by Species*/
proc summary data=sashelp.Fish;
var Weight;
class Species;
output out=summaryWeightSpecies;
run;
/*print output dataset*/
proc print data=summaryWeightSpecies;**

The output table displays the descriptive statistics for each Species of fish.

For example, we can observe the following descriptive statistics for just the Bream fish:

- The total number of observations was
**34**. - The minimum weight value was
**242**. - The maximum weight value was
**1,000**. - The mean weight value was
**626**. - The standard deviation of weight values was
**206.60**.

We can observe these descriptive statistics for every other species as well.

**Additional Resources**

The following tutorials explain how to perform other common tasks in SAS:

How to Calculate Correlation in SAS

How to Create Frequency Tables in SAS

How to Create Boxplots by Group in SAS