Transcript Introductory Workshop SPSS

SPSS Introductory Workshop
Humboldt State University
May 6, 2011
5/6/2011
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Sponsors
College of Arts, Humanities and Social Sciences
http://www.humboldt.edu/cahss/
and the
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SPSS Help Online

SPSS for Windows 16.0: A Basic Tutorial by
Linda Fiddler, Laura Hecht, Edward E. Nelson,
Elizabeth Ness Nelson, and James Ross.

Resources to Help You Learn and Use SPSS (UCLA)

SPSS Tutorials (Texas A&M)
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SPSS

A statistical package for beginning, intermediate, and
advanced data analysis

Other statistical packages include SAS and Stata

Online statistical packages that don’t require site
licenses include SDA
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Agenda



Introduction and Overview
A Brief Tour of SPSS
Creating Your Own SPSS Files or Opening Existing
Datasets
 Transforming data
 Recode
 Compute
 Select If
 Univariate analysis
 Frequencies
 Descriptives
 Explore
 Introduction to Graphics
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A Brief Tour of SPSS
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Data View
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Variable View
Variable Names
Variable Labels
Value Labels
MissingValues
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Menu Bar
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The Edit Menu
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The Edit Menu
(continued)
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The Data Menu
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The Transform Menu
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The Analyze Menu
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The Graphs Menu
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Opening SPSS
 Go
to start and find SPSS for Windows or look
for the SPSS icon on your desktop.
 Click
on SPSS 18.0 for Windows in
the Start menu or double click on the icon.
 You’ll need
to update your SPSS license every
year (or your school technician will do it for
you – Faculty/staff can load software on home
computers).
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Opening an Existing File

Often you will want to open a data set that you got
from someplace else.

These files will usually be in the form of a:
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SPSS portable file
SPSS data file
Raw data file with a SPSS syntax file
Raw data file without a syntax file
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SPSS Files and Extensions
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Portable file --
.por
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Data file --
.sav
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Output file --
.spo
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Syntax file --
.sps
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Opening a Portable (.por) file

Click on the open yellow folder
to open a new file.

Change file type to .por

Browse to where the portable file you want to open is
located and double click on that file.
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Opening SPSS – Syntax Window
Opening a Text file

Click on File > Read Text Data…

In the Open Data
window change
file type
Opening an Existing SPSS System File
Example: the 2010 General Social Survey

In browser, go to http://www.norc.org/GSS+Website/
 Select “Download” and “SPSS Format”
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Opening an Existing SPSS System File
Example: the 2010 General Social Survey

Select “2010”
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Opening an Existing SPSS System File
Example: the 2010 General Social Survey
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Select “OK” to “Save File”

Double Click on “2010.sav” file
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Saving an Existing SPSS System File
Example: the 2010 General Social Survey

Go to “File” and “Save As” and select “Variables”
button

Select “Drop All”
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Saving an Existing SPSS System File
Example: the 2010 General Social Survey

Select variables of
interest:
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Age
Cappun
Degree
Educ
Grass
Hrs1
Hrsrelax
Income06
Maeduc
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Marital
Masei
Paeduc
partyid
Pasei
Realinc
Relig
Sei
Sex
Saving an Existing SPSS System File
Example: the 2010 General Social Survey
Select “Continue” and “Save” (to either desktop or
your own flash drive)
 We will continue to work with this same GSS 2010
data file during the workshop

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Opening an Existing SPSS System File
Example: the 2008 General Social Survey

Open the file from network
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Opening an Existing SPSS System File
(continued)
 Opening


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the file:
Open from desktop (double-click) OR
Open SPSS first (as you would any windows
program), then navigate to file.
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Opening an Existing SPSS System File
(continued)

Move cursor to

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File
Open
Data

Click on Data
 Navigate to file
location (e.g.,
desktop) and open
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Transforming Data

We can transform variables by recoding, i.e.,
combining categories in an existing variable into
fewer categories.

We can also transform variables by creating new
variables out of existing variables.

We can select particular cases and analyze only these
cases.
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Recoding into Different Variables

Click on Transform > Recode > Into different variables.

Select the variable you want to recode. age
 Start by giving the new
variable a new name (age1)
 Click on Change
 Click on Old and New
Values
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Recoding age into AGE1

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
Use “Range” (fourth option down) to recode as follows.
Remember to click on “Add” after entering each recode.
18 to 29 = 1
30 to 49 = 2
50 to 69 = 3
70 to 89 = 4
Click Continue
And then OK.
Assign Value Labels to the
Four Categories of AGE1


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
Select the Variable View tab.
Scroll down the variables to age1 (at the bottom of the list).
In the Values column of age1 click on the small gray box.
Enter the first value followed by its label. Click Add.
Enter remaining 3 values.
Then click on OK.
18 to 29 = 1
30 to 49 = 2
50 to 69 = 3
70 to 89 = 4
Exercises for Recoding

Now recode income06 and call the new variable
income2
 This time use 8 categories: under $10K,
$10K to under $20K, $20K to under $30K,
$30K to under $40K, $40K to under $50K,
$50K to under $60K, $60K to under $75K,
and $75K and over

Add the value labels
 Run a frequency distribution for income2 and check
to make sure that you recoded it correctly by
comparing the unrecoded and recoded frequency
distributions
Creating a New Variable
with Compute
Let’s create a new variable and call it timewaste
which is the percentage of relaxation time (hrsrelax)
devoted to watching TV (tvhours)
 Click on Transform > Compute


Enter the new variable name (timewaste) into the
Target Variable box.
 Enter the formula for
this new variable
(100*tvhours/hrsrelax)
into the Numeric
Expression box.
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 Click on OK
Caution!

If, for any case, any of the variables used to create a
new variable has a missing value, the new variable
will automatically be assigned a missing value as
well.
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Exercise for Compute

The data file includes indexes of socio-economic
status for respondents (sei), their mothers (masei) and
their fathers (pasei).

Create an index of mobility by subtracting sei from an
average of masei and pasei.
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10 MINUTE BREAK!
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Using Select Cases to Select Specific
Cases for Analysis
Let’s select only Protestants for further analysis.
 Click on Data > Select Cases.


Click on “If condition is satisfied” and then
on the “If” button below it.
Using Select Cases to Select Specific
Cases for Analysis

Select the variable relig ( R’s RELIGEOUS PREFERENCE) and move
it into the box
on the right.

In this box, enter the
expression relig = 1.

Click on Continue
and on OK.
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Using Select Cases to Select Specific
Cases for Analysis

Note all cases not accepted
are crossed out on the left.

Again click on
Data > Select Cases.

Click on “all” and then
OK.
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Important Note on Using
Select Cases

When you are finished using Select Cases and
want to revert to using all the cases be sure to
click on Data > Select Cases and select All
cases. Then click on OK

If you don’t do this, you will continue to use
only those cases you last selected
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Exercises for Select Cases

Select all males (1 on the variable sex) and do a
frequency distribution for the variable partyid
(political party identification)
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Now select all females (2 on the variable sex) and run
a frequency distribution for partyid
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Is there a “gender gap” in party identification. How
large is it?

Note: same thing could have been done with
Crosstabs
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Univariate Analysis

Now that we know how to open existing files and
transform variables, we’re ready to begin analyzing
data

Univariate analysis refers to analyzing variables oneat-a-time
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Types of Univariate
Analysis Procedures
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
Frequencies

Descriptives

Explore
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Frequencies

Go to:
Analyze > Descriptive Statistics
> Frequencies

Select age1 and age

Notice Statistics and Charts
buttons at upper right and
Display frequencies tables
check-box at lower left
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Frequencies: Statistics

Click on Statistics
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Select the statistics you
want

Click on Continue
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Frequencies: Charts

Click on Charts

Select Histograms and
check With normal curve

Click on Continue

Click on OK
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Frequencies: Output - Tables
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Frequencies: Output - Statistics
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Frequencies: Output - Charts
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Exercises for Frequencies

Run frequency distributions for hrsrelax and tvhours
with appropriate statistics and charts

Run frequency distributions for cappun, grass, and
gunlaw with appropriate statistics and charts
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Descriptives

Click on
Analyze > Descriptive Statistics
> Descriptives

Select age and educ

Click on Options and
select the statistics you
want and then click on
Continue and OK
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Descriptives
(continued)
Descriptive Statistics
N
age AGE OF RESPONDENT
educ HIGHEST YEAR OF
SCHOOL COMPLETED
Valid N (listwise)
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Minimum
Maximum
Mean
Std. Deviation
4496
18
89
45.34
16.546
4502
0
20
13.25
3.213
4486
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Exercise for Descriptives

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Use Descriptives to compute the following
statistics for hrs1 (hours worked per week)
 Mean
 Standard deviation
 Variance
 Skewness
 Kurtosis
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More Exercises for Descriptives

Use Descriptives to compute the mean for educ,
maeduc, and paeduc

Who has the most education – respondents or
their parents?

Who has the most education – mothers or
fathers?
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Explore

Click on
Analyze > Descriptive Statistics
> Explore

Select hrs1 and put it in
the Dependent List

In the Display box on
the lower left, click on
Both
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Explore (continued)

Click on Statistics

Select the statistics you
want

Click on Continue
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Explore (continued)

Click on Plots
 Select the plots you
want
 Click on Continue
 Click on OK
Explore (continued)
Descriptives
Statistic
hrs1 NUMBER OF HOURS
WORKED LAST WEEK
Std. Error
Mean
42.13
95% Confidence Interval for Lower Bound
41.59
Mean
Upper Bound
42.66
5% Trimmed Mean
41.90
Median
40.00
Variance
Std. Deviation
208.271
14.432
Minimum
1
Maximum
89
Range
88
Interquartile Range
12
Skewness
Kurtosis
.272
.272
.046
1.243
.092
Explore (continued)
Descriptives
Statistic
hrs1 NUMBER OF HOURS
WORKED LAST WEEK
Std. Error
Mean
42.13
95% Confidence Interval for Lower Bound
41.59
Mean
Upper Bound
42.66
5% Trimmed Mean
41.90
Median
40.00
Variance
Std. Deviation
208.271
14.432
Minimum
1
Maximum
89
Range
88
Interquartile Range
12
Skewness
Kurtosis
.272
.272
.046
1.243
.092
Graphs: Bar Charts
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Click on
Graphs > Legacy Dialogs > Bar
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Graphs: Bar Charts
(continued)

Click on “Simple”

Click on “Define”
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Graphs: Bar Charts
(continued)

Click on “% of cases”

Drag or move
marital to
second box on right

Click on “OK”
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Graphs: Pie Charts

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Click on
Graphs > Legacy Dialogs > Pie
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Graphs: Pie Charts

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Click on “Define”
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Graphs: Pie Charts

Click on
“% of cases”

Drag or move
marital to
second box
on right

Click on “OK”
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Graphs: Box and Whiskers Plots
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Click on
Graphs > Legacy Dialogs > Boxplots
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Graphs: Box and Whiskers Plots
(continued)

Drag or move
tvhours to
first box on right

Drag or move
degree to
second box on right

Click on OK
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Graphs: Box and Whiskers Plots
(continued)
Extreme Values
(>3.0 X IQR)
Outliers
(1.5 – 3.0 IQR)
Median
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Box
(IQR)
Whiskers
(< 1.5 X IQR)
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Graphs: Scatterplots

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Click on
Graphs > Legacy Dialogs > Scatterplot
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Graphs: Scatterplots
(continued)

Click on “Simple Scatter”

Click on “Define”
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Graphs: Scatterplots
(continued)

Drag or move
maeduc to
first box on right

Drag or move
paeduc to
second box on right

Click on OK

Double-click on chart

Click on “Elements”
and “Fit Line at Total”
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Graphs: Histograms

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Click on
Graphs > Legacy Dialogs > Histogram
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Graphs: Histograms
(continued)

Drag or move
realinc to
first box on right

Check “Display
normal curve”

Click on OK
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