SPSS Intro and Analysis

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SPSSIntro and Analysis

• Hein Stigum
• Presentation, data and programs at
• http//folk.uio.no/heins/

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Analysis with SPSS

• SPSS introduction
• Files and menus
• syntax
• Analysis
• Continuous data
• Symmetrical
• Skewed
• Categorical data

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Files

• Data .sav Data Editor
• Syntax .sps Syntax Editor
• Output .spo ViewerChart Editor

Menus Toolbars Vary with file/editor Statusbar
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Data Editor

• Variable view
• Each variable name, type, label, value labels
• Data view
• Each case values
• Save a master file, work on workfile

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Syntax Editor

• Syntax
• Comands ends with a .
• Comments starts with

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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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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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Select and Filter
Do analysis on old people

• Method 1, select
• Select if (agegt50).
• Method 2, filter
• Compute ff(agegt50).
• Filter by ff.
• Filter off.

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Recode and label

• Cut age into 3 groups
• recode age (missingsysmis) (lowest thru 291)
  (30 thru 392) (40 thru highest3) into ageGr3.
• Add labels
• variable label ageGr3 Age in 3 groups.
• value label ageGr3 1?29 years 230-39 years
  3?40 years.
• Cut age into equal sized groups
• Rank age /ntiles(3) into ageGr3.
• Examine age by ageGr3 /plotnone.

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Compute and If
Compute ageSqrage2.
If (agelt50) old0. If (agegt50) old1.
Compute old(agegt50).
Comp oldMale0. If (agegt50 and sex1) oldMale1.
Compute oldMale (agegt50 and sex1).
Compute idcasenum.
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Missing

• System missing
• 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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Options

• Show variable names
• Edit, options, general, show names
• Show label values
• Edit, options, output labels, Values and Labels

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Analysis
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Datatypes

• Categorical data
• Nominal married/ single/ divorced
• Ordinal small/ medium/ large
• Numerical data
• Discrete number of children
• Continuous weight

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Data type dictates type of analysis
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Continuous symmetrical data
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Check for normality
graph /histogram(normal) debut.
pplot debut /typeQ-Q /distnormal.
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Describe continuous data
What is the distribution and the mean of weight?

• Distribution
• graph/histogram weight
• Describe
• descriptive weight

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Compare groups, equal variance?

• Equal

• Not equal

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Compare means
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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Test situations

• 1 sample test
• 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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Continuousskeweddata
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Partners
Percentiles 25 2 partners 50 (median) 5
partners 75 10 partners 90 20 partners
0
10
20
30
40
50
5
2
Number of lifetime partners
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Describe skewed data

• Medians and percentiles
• Analyze, Descriptive, Statisticsdescriptives and
  percentiles, PlotsBox

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Compare skewed distributions
Do boys and girls have the same height?

• 2 independent samples
• Analyze, Compare means, Means, height by sex,
  Optionsmedians
• Analyze, Non-parametric, 2 independent Samples,
  height by sex(1 2)
• K independent samples
• Analyze, Non-parametric, K independent samples

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Categoricaldata
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Describe and compare categorical data
Do boys and girls have the same educational plans?

• Frequency tables
• Analyze, Descriptives, Frequencies
• Crosstables
• Analyze, Descriptives, Crosstabs, Rowplans,
  Columnsex, Statchi, Cellscolumn

Syntax freq plans. cross plans by sex /cellscol
/statchi.
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Table of descriptives
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Table of tests