1. Introduction to SPSS Edward A. Greenberg, PhD
ASU HEALTH SOLUTIONS DATA LAB
January 7, 2013

2. Files for this workshop
Files can be downloaded from: or (with less typing):

3. SPSS Overview
SPSS Statistics is a software package used for statistical analysis.
It is now officially named "IBM SPSS Statistics".
SPSS uses a graphical user interface.
Most operations are “point and click”.

4. Availability of SPSS
Installed on most Health Solutions faculty and staff computers
Available via MyApps for installation on faculty, staff and student computers via University site license
Run in ASU Online Applications environment (Citrix) via MyApps
ASU Computing Sites on all campuses

5. Basic Steps in Data Analysis
Get your data into SPSS Statistics
SPSS can read data from a variety of sources.
Prepare your data set for analysis
Set variable attributes, clean your data and apply any needed transformations.
Select a procedure
Select a procedure from the menus to calculate statistics or to create a chart.
Select the variables for the analysis
The variables in the data file are displayed in a dialog box for the procedure.
Run the procedure and look at the results
Results are displayed in the Viewer.

6. Getting Data into SPSS Statistics
Open a previously saved SPSS Statistics data file
Read another type of file
Spreadsheet
Database
Text data file
Enter your data directly in the SPSS Data Editor

7. SPSS Data Files The SPSS Data Editor window has two views.
Data View shows a spreadsheet of cases (rows) and variables (columns).
Variable View displays the metadata dictionary, where each row represents a variable and shows the variable name, type, and other attributes.

8. SPSS Data Editor
Data View

9. SPSS Data Editor
Variable View

10. Variable Attributes ATTRIBUTE DESCRIPTION Name Variable name Type
Data type
Width
Number of digits or characters
Decimals
Number of decimal places
Label
Descriptive variable label
Values
Descriptive value labels
Missing
User‐defined missing values
Columns
Column width
Align
Alignment
Measure
Measurement level
Role
Role assignment

11. Variable Attributes VARIABLE NAME Variable names must be unique.
Variable names may be up to 64 characters in length.
Names can contain letters, numbers, or special characters.
Names must start with a letter #, or $.

12. Variable Attributes DATA TYPE Numeric String
40 character maximum length
Integers or numbers with decimals
Dates and times (various formats)
Other variations of numeric (currency, comma, scientific notation, etc.)
String
32,767 maximum length
Can contain any characters

13. Variable Attributes VARIABLE WIDTH
For numeric variables, the width of the number that is displayed.
String variables can be up to 32,767 characters long.

14. Variable Attributes DECIMALS
Number of decimal places displayed for numeric variables
Allowable values are 0 thru (width-1)

15. Variable Attributes VARIABLE LABEL A descriptive label for a variable
Up to 255 characters in length
Variable labels can contain spaces and reserved characters that are not allowed in variable names.

16. Variable Attributes VALUE LABELS
You can assign descriptive labels for each value of a variable
Particularly useful if your data file uses numeric codes to represent non-numeric categories (for example, codes of 1 and 2 for male and female)
Value labels can be up to 120 characters.

17. Variable Attributes MISSING VALUES
Allows you to distinguish between data that are missing for different reasons.
You can specify up to three discrete (individual) missing values, a range of missing values, or a range plus one discrete value.
Missing values are excluded from most calculations.
By default, an empty cell for a numeric variable is treated as missing.

18. Variable Attributes COLUMN WIDTH
The display width of a variable in the Data Editor
Affects only the display of values in the Data Editor
Does not change the defined width of a variable.
Column widths can also be changed in Data View by clicking and dragging the column borders.

19. Variable Attributes ALIGNMENT
Controls the display of data values and/or value labels in Data View
The default alignment is right for numeric variables and left for string variables.
This setting affects only the display in Data View.

20. Variable Attributes LEVEL OF MEASUREMENT LEVEL DESCRIPTION Nominal
Values represent categories with no intrinsic ranking.
Ordinal
Values represent categories with some intrinsic ranking.
Scale
Values represent ordered categories with a meaningful metric, so that distance comparisons between values are appropriate.

21. Variable Attributes ROLE
Some dialogs support predefined roles that can be used to pre-select variables for analysis.
Roles include Input (the default), Target, Both, None and several others.

22. Data Transformations
The Transform menu includes routines which perform transformations on selected variables. These include the following, among others:
TRANSFORMATION
DESCRIPTION
COMPUTE
Compute values for a variable based on numeric transformations of other variables
COUNT
Creates a numeric variable that, for each case, counts the occurrences of the same value
(or list of values) across a list of variables
RECODE
Allows you to reassign the values of existing variables or collapse ranges of existing
values into new values for a new or existing variable

23. Running Procedures Most procedures are accessed via the Analyze menu.
Procedures are grouped according to type, e.g., Reports, Descriptive Statistics, Compare Means, Tables, General Linear Model, and so on.

24. Running Procedures
Dialog boxes for statistical procedures and charts typically have two basic components:
Source variable list A list of variables in the active dataset. Only variable types that are allowed by the selected procedure are displayed in the source list.
Target variable list(s) One or more lists indicating the variables that you have chosen for the analysis, such as dependent and independent variable lists.

25. Results are displayed in the Viewer
SPSS Viewer
Results are displayed in the Viewer

26. SPSS Help and Other Resources
SPSS Help Menu

27. SPSS Help and Other Resources
Tutorial videos (in Flash format) are available from Central Michigan University at
Raynald Levesque maintains an excellent SPSS‐related web site with many helpful resources at
The CONHI Data Lab can help you with SPSS: NHI1 391, (602) 496‐DATA*
Many excellent books are available on SPSS
* probably is the best way to reach us