Mastering PROC MEANS in SAS: A Complete Guide for Statistical Summaries

When working with data in SAS, one of the most powerful and frequently used procedures is PROC MEANS. Whether you're summarizing your data before analysis or generating descriptive statistics for reporting, PROC MEANS provides a flexible and efficient way to get the job done.

In this post, we’ll dive deep into what PROC MEANS is, how to use it, and explore examples and tips to make the most of it in your data analysis workflow.

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🔍 What is PROC MEANS?

PROC MEANS is a SAS procedure used to calculate descriptive statistics such as:

• Mean
• Standard Deviation
• Minimum
• Maximum
• Sum
• Count (N)

It provides both default and customizable statistical summaries and can be used with grouping variables, class statements, and output datasets for further analysis.

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📌 Basic Syntax

PROC MEANS DATA=dataset-name <options>;
   VAR variable-list;
RUN;

Example:

proc means data=sashelp.class;
   var age height weight;
run;

This command summarizes the age, height, and weight variables from the sashelp.class dataset using default statistics.

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⚙️ Key Options in PROC MEANS

• N – Count of non-missing values
• MEAN – Arithmetic mean
• STD – Standard deviation
• MIN – Minimum value
• MAX – Maximum value
• SUM – Sum of values
• MEDIAN – Median
• QRANGE – Interquartile range
• MAXDEC= – Controls the number of decimal places

Example with Options:

proc means data=sashelp.class mean std min max maxdec=2;
   var height weight;
run;

This will return the mean, standard deviation, minimum, and maximum of height and weight rounded to 2 decimal places.

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🧮 Grouping Data: Using the CLASS Statement

If you want to group data by one or more categorical variables, use the CLASS statement.

proc means data=sashelp.class mean std;
   class sex;
   var height weight;
run;

This breaks down the statistics for height and weight by gender (sex variable).

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💾 Saving the Output: The OUTPUT Statement

To save the summary statistics to a new dataset for further use, use the OUTPUT statement.

proc means data=sashelp.class n mean std maxdec=2;
   var age height weight;
   output out=summary_stats
      n= n_age n_height n_weight
      mean= mean_age mean_height mean_weight
      std= std_age std_height std_weight;
run;

This stores count, mean, and standard deviation of each variable in a new dataset called summary_stats.

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🧑‍💻 Advanced Example: Multiple Grouping and Custom Output

proc means data=sashelp.class mean std;
   class sex age;
   var height weight;
   output out=multi_summary
      mean= mean_height mean_weight
      std= std_height std_weight;
run;

Here, we group the summary statistics by both sex and age, and save the mean and standard deviation of height and weight to the multi_summary dataset.

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💡 Tips and Best Practices

• Use CLASS instead of BY unless your data is already sorted. BY requires pre-sorted data.
• Use MAXDEC= to keep results readable. This is especially useful for reports.
• Store results with OUTPUT for further analysis or exporting.
• Combine PROC MEANS with PROC PRINT to display or filter specific outputs from your summary dataset.

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Pro TIP (Frequently asked Interview Question)

🆚 PROC MEANS vs. PROC SUMMARY

You might wonder: what’s the difference between PROC MEANS and PROC SUMMARY?

They are functionally similar. The key difference is:

• PROC MEANS displays output by default.
• PROC SUMMARY does not produce output unless the PRINT option is specified.

proc summary data=sashelp.class print;
   class sex;
   var height weight;
   output out=summary_data mean= std=;
run;