SPSS (Student Version) Help Guide
Download the Help Guide in Microsoft Word format

SPSS is similar to Microsoft Excel in terms of its layout. There is a menu and tool bar at the top of each window and many of the functions are the same as Excel. It is user friendly and best learned by doing. I recommend the use of the Tutorial which can be found in the Help menu. The following notes are a few introductory comments and tips to introduce you to the basics of SPSS.

The SPSS interface employs two windows: Program Editor and Viewer. Program Editor is where the data files are viewed and manipulated. Viewer is where the output of your statistical analyses is viewed and manipulated. Choose the Window menu to move back and forth between the Viewer and the Program Editor windows.

There are two basic types of files. The first is the data file (.sav). This is where all the data for your analyses resides. When you open up a data file, it will appear in the Program Editor window. The format is similar to a spreadsheet with a grid of rows and columns. The columns represent variables and the rows represent observations. You can place the cursor on the column heading to get a lengthier description of each variable. To get complete information on any variable, go to the Utilities menu and click on variables.

Data can be entered manually or imported from a database, spreadsheet, or text file. For the Marketing Management class, the data files already exist, so it is simply a matter of opening these files.

One important distinction between typical spreadsheet files and SPSS data files is that formulas cannot be entered directly into the sheet. To enter formulas in SPSS, go to the Transform menu and select compute. This allows you to calculate a new variable.

The second type of file is an output file (.spo). When a statistical procedure is run, output is produced. The Viewer window will automatically open to show the output. The left pane contains an outline view of the output. The right pane contains the contents of the output which include tables, charts, and text. There are book icons in the outline view next to the various objects of output. If the book is open, it indicates that the output is visible. If the book is closed, it is hidden. There are many ways to manipulate objects (hiding, moving, modifying charts, text, etc) in the output. I recommend going to "Working with output" in the tutorial to become more familiar with this.

There are many statistical procedures that can be run against the data. I’ve provided some details below on five that will be commonly used: Descriptives, Frequencies, Crosstabs, Correlations, and Regression.

The basic process is to select your procedure using the Analyze menu, select the variables that you wish to analyze, run the procedure, and analyze the results. For each procedure there are default settings for the statistics and output that can be modified by selecting Options in the dialog boxes.

1. Descriptives Analyze > Descriptive Statistics > Descriptives
   This is a useful procedure when initially working with a data file to provide a feel for the data. When running this procedure, a dialog box will appear in which you have to select the variables that you want for the procedure. Move variables from the left to the right into the variable list. The Ctrl button can be used to select multiple variables at a time. The default settings for this procedure will produce the mean, standard deviation, minimum, and maximum for each variable.

2. Frequencies Analyze > Descriptive Statistics > Frequencies
   This procedure is useful for categorical type values (nominal or ordinal). For each variable, it will produce the frequency, percent, and cumulative percent of each value. This output can also be produced in chart form by clicking on Charts in the dialog box. Click on Statistics in the dialog box to produce statistics.

3. Crosstabs Analyze > Descriptive Statistics > Crosstabs
   Crosstabs is effective for analyzing relationships between variables. It provides a two-way table or a multiway table if a layer is added. The rows and columns must be selected in the dialog box. The output can be viewed in terms of counts or percents and statistics can be produced. To use Crosstabs with non-categorical data, select the Transform menu and Categorize Variables.

4. Correlations Analyze > Correlate > Bivariate
   This procedure is useful to identify relationships between variables. The default selections will produce a correlation matrix with the correlation value, the significance of the relationship, and the number of observations used to calculate the correlation. Relationships that are significant at the 0.01 level are flagged with a ** and at the 0.05 level with a *.

5. Regression Analyze > Regression > Linear
   For regression analysis, the dependent variable must first be chosen. If you know the predictor variables that you wish to use, you can then select the independent variables. This analysis will produce a model summary that includes the R-squared value, an ANOVA table, and a coefficient table. Stepwise regression is effective when analyzing several variables and trying to determine the best predictor variables or the best regression model to use. Stepwise is an option under Method in the dialog box.