INTRODUCTION TO SPSS
(AND TIPS AND TRICKS)
CENTER FOR SOCIAL SCIENCE
COMPUTATION AND RESEARCH
(CSSCR)
UNIVERSITY OF WASHINGTON
Fall Quarter, 2012
Prepared by Eric Hamilton
TOPICS COVERED IN THIS
INTRODUCTORY COURSE
-SPSS basic structure & layout
-Importing data
-GUI vs. Syntax use
-Managing and recoding your data
-Descriptive statistics & intro analysis–
frequencies, explore, crosstabs, correlations
-Tips and tricks for data management and
analysis
-Resources for learning more about SPSS
SPSS AT A GLANCE
SPSS (Statistical Package for the Social Sciences)
offers a user-friendly data analysis platform.
Go to START, PROGRAMS, and click on the SPSS
version of your choice
or
The computers in the CSSCR labs typically have
SPSS on the desktop. Double click on the icon of
the version that you want to use.
BASIC STRUCTURE OF SPSS
SPSS has three windows for working
with data:
The Data Editor Window (.sav)
shows data in two forms:
Data view
Variable view
The Output Viewer Window (.spv)
shows results of data analysis
The Syntax Editor Window (.sps)
shows the syntax command script.
This is also where you can type
and run your own syntax
commands.
Note: Perform separate save procedures for the data editor (.sav), output
viewer (.spv), and syntax editor (.sps) windows.
Remember to save your work frequently, under names that will have
meaning for you in the future.
THE EDITOR WINDOW:
DATA VIEW VS. VARIABLE VIEW
Data view
Rows are cases (participants in the study)
Columns are variables
You can toggle between data values and labels
Variable view
Rows define the variable characteristics:
Name, Type, Width, Decimals, Label, Values, Missing,
Columns, Align, Measure.
The Measure of variables in the dataset is important:
 Scale = “continuous” – e.g., age, weight, income
 Ordinal = “ordered” – categories that can be ranked
(e.g., level of satisfaction or agreement, Likert-type scales)
 Nominal = “names” – categories that cannot be
ranked (e.g., ID number)
IMPORTING A DATA FILE
-You can work with the Wizard, or click Cancel, and
-Select File > Open > Data.
-Locate the folder that contains your data file.
-Select the format of your incoming data with the “Files
of type” button
-locate and select your data file, then click Open
-a window will appear, and ask whether the first row in
the data set represents variable names (Yes), click OK
-Check to see that the data appear as in your original
data set
*For the examples covered in this presentation, select
“Files of type: Excel”, then open
“CSSCR_Aut12_SPSSintro.xls”
GUI VS. SYNTAX
The GUI (graphical userinterface, “gooey”) allows you
to interact with SPSS via
images and buttons, rather
than text. You can “draw-down”
commands from menus at the
top of the window.
The Syntax window executes
commands that you enter as
text.
Open a syntax window (File >
Open > Syntax), and type or
paste text to call functions.
Select specific sections of text
and click “Run Selection” to
execute commands.
SELECTING CASES
With the select cases
command, you can select
subsets of cases for analysis
DATA > SELECT CASES > IF
CONDITION IS SATISFIED
-select the variable of interst
-enter the logical command to
select the cases you want to
analyze
e.g., “Select Cases IF Grade =
12”
COMPUTE VARIABLE
Example: create a new, transformed
variable from an already existing
variable
-click Transform > Compute Variable
-Assign the new “Target Variable” (this
will be attached at the end of the
variables list)
Let’s call it: TestScore_Ex
-fill in the numeric expression:
TestScore = SQRT(TestScore)
To compute, for example, only the 12 th
grade scores, you can create an If Then statement by clicking on the IF
button
-click INCLUDE IF CASE SATISFIES
CONDITION, and enter (e.g.) Grade =
12, then click OK
COMPUTE VARIABLE (CONTIN.)
-if you need to find how to write
the function, there is a list of
functions on the right
This procedure will create a
new variable at the end of the
variable list that is the means
of the variables that you
chose to include in the
computation.
-again, you can select a subset
of cases by by clicking on the
IF button
RECODING VARIABLES
Recoding allows a
researcher to create a new
variable with, for example, a
different set of parameters
-Decide which Variable(s)
you want to recode
TRANSFORM > RECODE
INTO
DIFFERENT VARIABLE
-move variable of interest to
the right
-create a name for the new
variable
-click Old and New Values
RECODING VARIABLES (CONTIN.)
-Select and enter the
appropriate data recode
modifications:
-Enter an already existing Old
Value, then enter its New
Value, and click Add
(note: these must be typed
exactly as they appear in the
data view. Copy/paste is ok.)
-Alternatively, click RANGE to
create ranges of old values
-If you’ve recoded all the values you want changed,
click on “Copy old value(s)”
-Click OK and check that your new values were
created correctly.
THE VARIABLE VIEW:
EDITING VALUE LABELS
After recoding your variables, you
may want to record the values
assigned to each category of the
variables. You can note in
SPSS what your numeric values
stand for in the “Value Labels”
area.
-Select the Values drop-down,
and record the values and labels
for your range of new data.
-If you forget how you recoded
your data, your labels should be
available in your output (.spo)
file.
THE VARIABLE VIEW:
ACCOUNTING FOR MISSING DATA
Many data sets have a few, or a lot, of missing
data points.
SPSS lets you account for missing data in two
ways: system-missing (indicated by one
period in the data cell); and user-defined
(specified by you, User).
Click on a variable’s “missing” drop-down, and
enter the specific, discrete values (998, 999,
etc.) that will represent missing data in your
data set.
A range can also be used if, for example, you
only want to use half of a scale.
Also, system-missing data is assigned by
SPSS when a function cannot be performed.
(e.g., dividing a number by zero)
DESCRIPTIVE STATISTICS:
FREQUENCIES
-Lets say we want output on the
number of cases (the
frequencies) subjected to each
type of curriculum in the
example dataset.
Click ANALYZE > DESCRIPTIVE
STATISTICS > FREQUENCIES
-Choose Curriculum from the list.
-Select desired statistical output (Central Tendency,
Dispersion, etc.) from the Statistics button.
-Select the type of chart you’d like SPSS to produce (e.g.,
Histogram) with the Charts button.
-Click OK, or Paste (then Run), and review the output.
DESCRIPTIVE STATISTICS:
EXPLORE
You can also generate a variety
of descriptive statistics on
multiple variables at once.
SPSS can produce a lot of
useful statistical output with the
Explore command.
Click ANALYZE > DESCRIPTIVE
STATISTICS > EXPLORE
-Decide which relationships,
independent variables (Factors)
to outcomes (Dependent), you’d
like SPSS to produce, and
move them over with the arrows
-Click Statistics/Plots/Options to choose which
statistics and forms of output you are interested in
producing, then click OK or Paste to Syntax.
-Review your output.
DESCRIPTIVE STATISTICS:
CROSSTABS
To look at frequencies of data
nested across multiple variables
(and run a Chi-Square test):
ANALYZE > DESCRIPTIVE
STATISTICS > CROSSTABS
-Move the variables of interest
over with the arrows
-Select the options you would like
to apply to the Crosstabs output
(Statistics, etc.)
-Click OK (or PASTE to syntax)
CORRELATION ANALYSIS
This measures the dependence
between two variables, by the
Pearson product-moment
correlation coefficient, or
"Pearson's correlation”
-ANALYZE > CORRELATE >
BIVARIATE
-Move the variables of interest over
with the arrow
-Select the options you woul d like to
apply to the correlation analysis
(Statistics, etc.)
-Select Two-tailed significance test,
if the direction of the relationship
between your variables is unknown
-Click OK (or PASTE to syntax)
SAVING YOUR WORK
After all the data cleaning and various forms of
analyses you’ve run, you want to be sure to
save all of your work, in an organized fashion
(and regularly)!
-Give your data files names that are sufficiently
descriptive of what you are working on, and
that you will recognize when you come back to
the data at some time in the future.
-Backup your data (save in multiple locations:
memory sticks, computers, ext. hard drives,
etc.), in case one source should become lost
or corrupted.
SAVING YOUR WORK (CONTIN.)
Remember that each file format (. sav, .spv, .sps)
should be saved as a uniquely-identified element of
your data cleaning/analyses.
It may be useful, during the process of data cleaning
and analyzing, to save your work with ascending file
names.
for example:
School1_datacleaning_A1.sav
School1_datacleaning_A2.sav
…
School1_datacleaning_B1.sav
This way, you can delete older, unneeded files, and
you have a backup if something goes wrong (the
program stalls, earthquake, etc.). 
TIPS AND TRICKS
FOR USING SPSS
 Keep Variable Names short. Use Labels as a more detailed
description of your data
 Toggle between data values and labels:
 Double-click margins to move between Data and Variable Views
 Right-click in drawdown menus (e.g., transform operations) to
toggle between values/labels
 Moving variables within the list in Variable View
 “clearing the cursor”
 Click-and-hold, move right to move a new variable to the top of the file
 Utilities option: Data File Comments tool (very useful!). This
function auto-dates your entries, and remains in files saved
from previous files
 Other ideas?
HELPFUL RESOURCES
CSSCR has a Quicktime SPSS class and SPSS handouts
on the CSSCR website.
There are many resources online to help you learn SPSS
(tutorials, blogs, etc.). Here are a few examples:
 http://www.stat.tamu.edu/spss.php
 http://www.ats.ucla.edu/stat/SPSS/
 http://www.lrz.de/~wlm/wlmspss.htm
CSSCR offers classes on SPSS frequently – come back
for an Intermediate SPSS class or call us to schedule
an appointment with one of the CSSCR consultants!
WHAT WE HAVE COVERED:
-SPSS basic structure & layout
-GUI vs. syntax use
-Importing data
-Managing and recoding your data
-Descriptive statistics – frequencies, explore,
crosstabs, correlations
-Tips and tricks for data management and
analysis
-Resources for learning more about SPSS
INTRODUCTION TO SPSS
(AND TIPS AND TRICKS)
Thanks!
CENTER FOR SOCIAL SCIENCE
COMPUTATION AND RESEARCH (CSSCR)
UNIVERSITY OF WASHINGTON
Fall Quarter, 2012
Prepared by Eric Hamilton