Descriptive statistics can be used to summarize the data. If your data is categorical, try the frequencies or crosstabs procedures. If your data is scale level, try summaries or descriptives. If you have multiple response questions, use multiple response sets.

The Summarize procedure can be used to get descriptive information about data. You will probably want to turn off the "Display Cases". Place the variables you want summarize in the "Variables" section and any grouping variables (if needed) in the "Grouping Variables" section.

In this example, I will get summary statistics on the height broken down by gender and favorite grocery store.

You can specify which statistics you want for the "Variables". In this case, I have selected N (number of cases), the mean, median, minimum, maximum, and standard deviation. Click "continue" when done selecting.

You may see the output of the Summarize procedure.

The Frequencies procedure works better with categorical data than with scale data. It will tell you how many times each value appears in the data. You can include means, medians, etc, but that really doesn't make sense with nominal data.

In this example, I will be getting frequency counts for two variables, gender and favorite season. You can request bar charts, pie charts, or histograms by clicking on the "Charts" button although I have not in this example.

You can see the output from the Frequencies procedure.

The Descriptives procedure gives descriptive statistics for the variables. It is geared more towards scale data rather than nominal or ordinal data, although you can get descriptive statistics for that level of measurement, also.

Click the "Options" button to specify which statistics you want computed.

You can view the output from the Descriptives procedure.

The Crosstabs procedure is useful for generating the joint frequencies between different variables. Like the frequencies procedure, this works best with categorical data.

In this example, I want to see the how the favorite season compares to the favorite grocery store.

One use of "Statistics" is to perform a chi-square test for independence. This would test if the season and grocery store are independent of each other. Of course, our sample size is really too small to tell anything, but this may be useful in the future.

See the output from the Crosstabs procedure.

This is similar to the frequencies or crosstabs procedure except that you can define sets containing multiple responses.

In this example, I have created a set called "food" that includes all eight of the food choices.

You may see the output from the Tables procedure.

This can be used to generate summary statistics, but requires a dependent and independent variable.

This command will give the means for the heights, grouped by the gender.

You may see the output of the Means procedure.