1. SPSS Intro and Analysis
Hein Stigum
Presentation, data and programs at:

2. Analysis with SPSS SPSS introduction Analysis Files and menus syntax
Continuous data
Symmetrical
Skewed
Categorical data
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3. Files Data .sav Data Editor Syntax .sps Syntax Editor
Output .spo Viewer+Chart Editor
Menus
Toolbars Vary with file/editor
Statusbar
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4. Data Editor Variable view Data view
Each variable: name, type, label, value labels
Data view
Each case: values
Save a master file, work on workfile
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5. Syntax Editor Syntax Comands ends with a ”.” Comments starts with ”*”
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6. Ways of working Use menus to run commands
Use menus, paste commands, run
Write commands, run
Your main product: ”The Syntax File” !!
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7. Viewer Contains all output Show/hide or delete elements
Double-click to edit element
Double-click on chart to start Chart Editor
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8. Select and Filter Method 1, select Method 2, filter
Do analysis on “old people”:
Method 1, select
Select if (age>50).
Method 2, filter
Compute ff=(age>50).
Filter by ff. …
Filter off.
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9. Recode and label Cut age into 3 groups Add labels
recode age (missing=sysmis) (lowest thru 29=1) (30 thru 39=2) (40 thru highest=3) into ageGr3.
Add labels
variable label ageGr3 ’Age in 3 groups’.
value label ageGr3 1’29 years’ 2’30-39 years’ 3’40 years’.
Cut age into equal sized groups
Rank age /ntiles(3) into ageGr3.
Examine age by ageGr3 /plot=none.
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10. Compute and If Compute ageSqr=age**2. If (age<=50) old=0.
Compute old=(age>50).
Comp oldMale=0.
If (age>50 and sex=1)
oldMale=1.
Compute oldMale=
(age>50 and sex=1).
Compute id=$casenum.
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11. Missing System missing User missing Selection
Empty values are marked ”.” and called sysmis
User missing
Set to missing: missing age (999).
Set to value: missing age ().
Selection
Remove all missing: select if (not missing(age))
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12. Options Show variable names Show label values
Edit, options, general, show names
Show label values
Edit, options, output labels, Values and Labels
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13. Analysis

14. Datatypes Categorical data Numerical data
Nominal: married/ single/ divorced
Ordinal: small/ medium/ large
Numerical data
Discrete: number of children
Continuous: weight
Coding 1, 2, 3, is 2 twice as much as 1
1. Set of methods for categorical data
proportion married
1. Set of methods for numerical data
average weight
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15. Data type dictates type of analysis
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16. Continuous symmetrical data

17. Check for normality Deviations form normal
graph /histogram(normal) debut.
pplot debut /type=Q-Q /dist=normal.
Syntax
If normal: close to the diagonal
May check for other distrbutions: dist=...
Deviations form normal
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18. Describe continuous data
What is the distribution and the mean of weight?
Distribution
graph/histogram weight
Describe
descriptive weight
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19. Compare groups, equal variance?
Not equal
Compare boys and girls
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20. Compare means T-test Anova
Do boys and girls have the same average weight?
T-test
Analyze, Compare means, Independent-Samples T-test
Anova
Analyze, Compare means, One-Way ANOVA
Options, homogeniety of variance test
Does weight vary with social group? (3 or more groups)
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21. Test situations 1 sample test 2 independent samples
Weight =10
2 independent samples
Weight by sex
K independent samples
Weight by age groups
2 dependent samples (Paired)
Weight last year = Weight today
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22. Continuous skewed data

23. Partners Percentiles: 25% 2 partners 50% (median) 5 partners
25., 50., 75. and 90. percentile
Mean
Antall partner i løpet av livet 2 5 10 20 30 40 50
Number of lifetime partners
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24. Describe skewed data Medians and percentiles
Analyze, Descriptive, Statistics=descriptives and percentiles, Plots=Box
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25. Compare skewed distributions
Do boys and girls have the same height?
2 independent samples
Analyze, Compare means, Means, height by sex, Options=medians
Analyze, Non-parametric, 2 independent Samples, height by sex(1 2)
K independent samples
Analyze, Non-parametric, K independent samples
Do similar test for drunk by physical activity a2_4_1 (1 4) K ind samples
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26. Categorical data

27. Describe and compare categorical data
Do boys and girls have the same educational plans?
Frequency tables
Analyze, Descriptives, Frequencies
Crosstables
Analyze, Descriptives, Crosstabs, Row=plans, Column=sex, Stat=chi, Cells=column
May add barchart with percentages to freq.
May add barchart to cross, but not with percentages
Syntax:
freq plans.
cross plans by sex /cells=col /stat=chi.
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28. Table of descriptives
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29. Table of tests
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