Transcript Introduction to SPSS - CSSCR

Introduction to SPSS
(For SPSS Version 16.0)
Eric Hamilton
CSSCR
CENTER FOR SOCIAL SCIENCE COMPUTATION AND
RESEARCH
UNIVERSITY OF WASHINGTON
Fall, 2010
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
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 2009. This
tutorial refers to use of SPSS 16.0. There are some
added functions in the new version, but for the
most part, the usability is similar.
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.
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.
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.
Data view vs. Variable view
Data 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)
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.
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.
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
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
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.
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.
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
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.
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.
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
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.
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
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.
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
Other Resources
There are many resources online to help you learn SPSS
(tutorials, blogs, etc.)
http://www.stat.tamu.edu/spss.php
http://www.ats.ucla.edu/stat/SPSS/
http://www.lrz.de/~wlm/wlmspss.htm
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.
Introduction to SPSS
(For SPSS Version 16.0)
Eric Hamilton
CSSCR
CENTER FOR SOCIAL SCIENCE COMPUTATION AND
RESEARCH
UNIVERSITY OF WASHINGTON
Fall, 2010