SPSS TutorialsDescriptives

Descriptives is best to obtain quick summaries of numeric variables, or to compare several numeric variables side-by-side.

Descriptives

The Descriptives procedure can produce a select number of descriptive statistics on any variable. (Note, however, that the descriptive statistics generated are only suitable for numeric scale variables). The Descriptives procedure is best used when you want to compare the descriptive statistics of several numeric variables side-by-side.

To run the Descriptives procedure, select Analyze > Descriptive Statistics > Descriptives.

The Descriptives window lists all of the variables in your dataset in the left column. To select variables for analysis, click on the variable name to highlight it, then click on the arrow button to move the variable to the column on the right. Alternatively, you can double-click on the name of a variable to move it to the column on the right.

Selecting the Save standardized values as variables check box will create new variables containing the standardized values of each of the input variables. (Recall that the standardized value of a variable is computed by subtracting the mean of the variable, then dividing the difference by the standard deviation.)

By default, the Descriptives procedure computes the mean, standard deviation, minimum, and maximum of the variable. Clicking Options will allow you to disable any of the aforementioned statistics, or enable sum, variance, range, standard error of the mean (S.E. mean), kurtosis, and skewness. You can also choose how you want the output to be organized:

• Variable list will print the variables in the same order that they are specified in the Descriptives window.
• Alphabetically will arrange the variables in alphabetical order.
• Ascending means will order the output so that the variables with the smallest means are first and the variables with the largest means last.
• Descending means will order the output so that the variables with the largest means are first and the variables with the smallest means are last.

Problem Statement

The sample dataset has test scores (out of 100) on four placement tests: English, Reading, Math, and Writing. We want to compare the summary statistics of these four tests so we can determine which tests the students tended to do the best and the worst on.

Click Analyze > Descriptive Statistics > Descriptives, then double click on the variables English, Reading, Math, and Writing in the left column. Click OK when finished.

Output

Syntax

DESCRIPTIVES VARIABLES=English Reading Math Writing
/STATISTICS=MEAN STDDEV MIN MAX.

Tables

Here we see a side-by-side comparison of the descriptive statistics for the four numeric variables. This allows us to quickly make the following observations about the data:

• Some students were missing scores for the English test.
• The maximum scores observed on the English and the Reading tests exceed 100 points, which was supposed to be the maximum possible score. This could indicate a problem with data entry, or could indicate an issue with the scoring method. Before proceeding with any other data analysis, we would need to resolve the issues with these measurements.
• The minimum Math score was far lower than the minimum scores for the other sections of the test.
• The averages of the English and Reading scores were very close.
• Math had the lowest average score of the four sections, but the highest standard deviation in scores.