1. Introduction to SPSS (For SPSS Version 16.0)
Eric Hamilton
CSSCR
CENTER FOR SOCIAL SCIENCE COMPUTATION AND RESEARCH
UNIVERSITY OF WASHINGTON
Fall, 2010

2. Topics Covered in this Introductory Course
SPSS at a glance, basic structure
Cleaning & reformatting your data
Descriptive statistics – frequencies, crosstabs, explore
Charts & graphs: histograms, legacy charts, editing graphs
Resources for learning more about SPSS

3. SPSS at a glance
SPSS (Statistical Package for the Social Sciences) was designed to offer a more user-friendly data analysis presentation than other statistical software (e.g., S-Plus, R, SAS).
The newest version of SPSS is called “IBM SPSS Statistics 19”. IBM purchased SPSS in This tutorial refers to use of SPSS There are some added functions in the new version, but for the most part, the usability is similar.

4. Opening SPSS Go to START, PROGRAMS
The computers in the CSSCR lab typically have SPSS on the desktop. Select the red box that says SPSS on the top.

5. Opening a data file in SPSS
Open the version of SPSS you’d like to work with.
Select File>Open>Data.
Select the format of your data with the “Files of type” menu, then locate, select, and open your data file.

6. Basic structure of SPSS
There are multiple windows in SPSS
The Data Editor Window – shows data in two forms
Data view
Variable view
The Output Viewer Window – shows results of data analysis
The Syntax Editor Window – shows the syntax command script. This is also where you can type your own syntax commands and run them.
Note: you must perform separate save procedures for the data editor (.sav), output viewer (.spv), and syntax editor (.sps) windows.

7. Data view vs. Variable view
Rows are cases
Columns are variables (generally speaking)
Variable view
Rows define the variables
Name, Type, Width, Decimals, Label, Values, Missing, Columns, Align, Measure.
The Measure of variables in the dataset is important:
Scale “continuous” – age, weight, income
Nominal “names” – categories that cannot be ranked (ID number)
Ordinal “ordered” – categories that can be ranked (level of satisfaction)

8. Data manipulation – select cases
With the select cases command, you can select specific cases for analysis
click DATA
click SELECT CASES
click IF CONDITION IS SATISFIED
select the variable with which you’ll select cases
enter the logical command to select the cases you want to analyze.

9. Data manipulation – compute new variable
Example: create a new variable from already existing variables
click TRANSFORM
click Compute Variable
fill in the new target variable testscore_ex
fill in numeric expression = StTestScore + 3
create an IF statement by clicking on the IF button
click INCLUDE IF CASE SATISFIES CONDITION, and enter SCHOOL = LOCKE, then click OK
Hypothetically, this new variable testscore_ex would adjust scores for those students who were at Locke and took a modified version of the test.

10. Data manipulation – recode a variable
Recoding allows a researcher to create a new variable with a different set of parameters
click TRANSFORM
click RECODE INTO DIFFERENT VARIABLE
move Grade over to the right
create a name for the new variable: Grade_num
click Old and New Values

11. Data manipulation – recode a variable (contin.)
Select and enter data recode modifications:
Enter an already existing Old Value, then enter its New Value, and Add or,
then click RANGE to create ranges of old values
click VALUE to create a new value for that range of old values

12. Cleaning your data: missing data
There are two types of missing values in SPSS: system-missing and user-defined.
System-missing data is assigned by SPSS when a function cannot be performed.
For example, dividing a number by zero. SPSS indicates that a value is system-missing by one period in the data cell.

13. Cleaning your data – missing data
User-defined missing data are values that the researcher can tell SPSS to recognize as missing. For example, 9999 is a common user-defined missing value. To define a variable’s user-defined missing value…
Look at your variables in VARIABLE VIEW
Find the column labeled MISSING
Find the variable that you would like to work with.
Select that variable’s missing cell by clicking on the gray box in the right corner.
click DISCRETE MISSING VALUES
enter a specific value, such as 9999, to define this variable’s missing value
A range can also be used if, for example, you only want to use half of a scale.

14. Cleaning your data – missing data cont.
When you have missing data in your data set, you can fill in the missing data with surrounding information so that the missingness does not impede your analysis.
click TRANSFORM
click REPLACE MISSING VALUES
select the variable with missing values and move it to the right using the arrow
SPSS will rename and create a new variable with your filled-in data.
click METHOD to select what type of method you would like SPSS to use when replacing missing values.
click OK and view your new data in data view

15. Descriptive Statistics: Frequencies
Lets say we are interested in learning more about the characteristics of the schools (School) in the example dataset.
Click ANALYZE
Click DESCRIPTIVE STATISTICS
Click FREQUENCIES
Choose School from the list.

16. Descriptive Statistics: Explore
You can also generate descriptive statistics on multiple variables at once.
Click ANALYZE
Click DESCRIPTIVE STATISTICS
Click EXPLORE
Move the variables you’re interested in over with the arrow
Click Statistics/Plots/Options to choose which statistics and forms of output you are interested in seeing.

17. Descriptive Statistics: Crosstabs
To generate descriptive statistics to look at frequencies across multiple variables:
Click ANALYZE
Click DESCRIPTIVE STATISTICS
Click CROSSTABS
Move the variables you’re interested in over with the arrow
Select the options you’d like to apply to the Crosstabs output (Statistics, etc.)
Click OK

18. Graphing Data Graphs can be generated and formatted easily in SPSS.
Click GRAPH
Click LEGACY DIALOGS
Click HISTOGRAM
Put School on the X axis.
Click ELEMENT PROPERTIES. Check the box labeled DISPLAY NORMAL CURVE. This will impose a normal curve onto your graph. You can also change the style of your graph in this element properties window.
These graphs can be copied and pasted into other programs, such as Word and Excel.

19. Graphing Continued
Graphs can also be gererated through the Frequencies command:
Click ANALYZE
Click DESCRIPTIVE STATISTICS
Click FREQUENCIES
Click School
Click CHART
Click BAR CHART
Click PERCENTAGES

20. Formatting Graphs
You can easily make your graphs clearer and more professional-looking with SPSS
Double click on the graph or chart in the output window, this opens the chart editor.
Double click on the part of the chart you want to edit.
Select and adjust the various properties until your chart appears as you wish
You can adjust the scale, labels, text, etc.

21. What we have covered: SPSS at a glance: basic structure of SPSS
Cleaning & transforming your data – select cases, sorting, recoding, transforming
Descriptive statistics – frequencies, crosstabs, explore
Charts & graphs: legacy charts, editing graphs

22. Other Resources
There are many resources online to help you learn SPSS (tutorials, blogs, etc.)
CSSCR has a Quicktime SPSS class and SPSS handouts on the department website.
CSSCR offers classes on SPSS frequently– come back for the SPSS Beyond the Basics class, or schedule an appt. with on of the CSSCR consultants.

23. Introduction to SPSS (For SPSS Version 16.0)
Eric Hamilton
CSSCR
CENTER FOR SOCIAL SCIENCE COMPUTATION AND RESEARCH
UNIVERSITY OF WASHINGTON
Fall, 2010