SPSS Intermediate Workshop

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SPSS Intermediate Workshop

• Cal Poly, Pomona
• February 13, 2009

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Sponsors

• http//www.academic.csupomona.edu/facultycenter/
  
• and the
• http//www.ssric.org

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Facilitators

• Gene Turner (CSU Northridge, Geography)
• John Korey (Cal Poly Pomona, Political
  Science)

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Agenda for the Intermediate SPSS Workshop

• Cross tabulations
• Bivariate
• Multivariate
• Comparing means
• Independent sample t test
• Paired-sample t test
• One-way analysis of variance
• Regression and correlation
• Bivariate
• Multivariate
• Graphs

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Opening the Data Files (.sav) for this Workshop

• The data files were going to use in this
  workshop are .sav files.
• One of the data sets that were going to use comes
  with the text gss06a.sav. You can download it
  from the web site that has the text
  http//www.ssric.org/tr/onlinetextbooks. Look
  for Right click here to download GSS06A.

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Opening the Data Files (.sav) for this Workshop
(contimued)

• Were also going to use the states data set, a
  file with information about each of the 50
  states. You can download it from
  http//www.csupomona.edu/jlkorey/POWERMUTT/Data,
  and can download a codebook describing it from
  http//www.csupomona.edu/jlkorey/POWERMUTT/Codeb
  ooks/states.html.

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Choosing options within SPSS

• Click on Edit and Options.
• Under Variable Lists, check Display Names and
  Alphabetical.
• Under Output Labels, select Names and Labels
  in the first box, and Values and Labels in the
  second.
• Under File Locations, choose where and how you
  wish to save the session journal (syntax) file.

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Cross Tabulations(see chs. 5 and 8 in text)

• Analyzes association between data categories
  especially nominal and ordinal data
• Compares observed counts in each cell to an
  expected count
• Requires a count of at least 5 in each cell

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Cross Tabulations(see chs. 5 and 8 in text)
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Cross Tabulations(see chs. 5 and 8 in text)

• Click on Analyze gt Descriptive Statistics gt
  Crosstabs.
• Select PRES04 as the row variable, and SEX and
  MARITAL as column variables.
• Click on Cells and check Column.
• Click on Statistics and check Cramers V.
• Click on OK.

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Cross Tabulations(with a control variable)

• Click on Analyze gt Descriptive Statistics gt
  Crosstabs
• Move SEX from second to third dialog box.
• Click on OK.

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Copying the Table

• Select the table by single clicking on it.
• Click on Edit and then on Copy.
• Go to your report in Word and click on Edit gt
  Paste Special gt JPEG gt OK.

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Exercises for Crosstabs

• Using the gss06a.sav data, crosstabulate actual
  income (INC06REC) and perceived income (FINRELA),
  treating the later as your dependent variable.
  Use Kendalls tauc to measure association.
• Use crosstabs to test a hypothesis of your
  choosing.

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Ways to Compare Means(see ch. 6 in text)

• Independent-sample t test
• Paired-sample t test
• One-way analysis of variance

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Computing Means

• Click on Analyze/Compare Means and then on Means.
• Move AGEKDBRN into the Dependent List.
• Move SEX into the Independent List
• Click on OK.

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Computing Means (continued)

• Requesting other statistics click on Options
  and select the other statistics you would like.
• Further breakdowns Click on Next and select a
  further breakdown.
• Move MARITAL into the box and click on OK.

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Exercises for Comparing Means

• Compute the mean age (AGE) of respondents who
  voted for Bush, Kerry, and someone else (PRES04).
  Which group had the youngest mean age and which
  had the oldest mean age?
• Compute the mean number of hours that people with
  different levels of education (DEGREE) watch
  television (TVHOURS). Who watches more
  television those with less education or those
  with more education?

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Independent Sample T Test

• Independent samples are samples where the
  composition of one sample does not influence the
  composition of the other sample.
• Click on Analyze/Compare Means/Independent Sample
  T Test.
• Select the variable that defines the two groups.
  This is called the Grouping Variable. Lets
  use SEX as our grouping variable.
• Click on Define Groups and indicate the values
  that define the two groups. Males are coded 1
  and females are coded 2.
• Click on continue.

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Independent Sample T Test

• Select the Test Variable. This is the variable
  that you want to use to compare the two groups.
  Lets use AGEKDBRN as our test variable.
• Click on OK.

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Exercises for Independent Sample T Test

• Use the independent sample t test to compare the
  mean age (AGE) of respondents who believe and do
  not believe in life after death (POSTLIFE).
  Which group had the highest mean age? Was the
  difference statistically significant at the .05
  level of significance?
• Compare the mean family income (INCOME06) of men
  and women (SEX). Who had the higher income? Was
  it statistically significant at the .05 level of
  significance?

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Paired Samples T Test

• Paired samples are samples where the composition
  of one sample determines the composition of the
  other sample (e.g., sample of husbands and wives
  married to each other).
• Click on Analyze/Compare Means/Paired Samples T
  Test.

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Paired Samples T Test (continued)

• Select your paired variables by clicking on the
  first variable in the list on the left and then
  clicking on the arrow. Then click on the second
  variable and click on the arrow again. They
  should now be in the Paired Variables box on
  the right. Lets use MAEDUC and PAEDUC as our
  paired variables.
• Move these two paired variables to the Paired
  Variables box.
• Click on OK.

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Exercises for Paired Sample T Test

• Use the paired-sample t test to compare mothers
  socioeconomic status (MASEI) and fathers
  socioeconomic status (PASEI). Who has the
  highest mean socioeconomic status mothers or
  fathers? Was the difference statistically
  significant?
• Compare the mean years of school completed for
  respondents (EDUC) and their spouses (SPEDUC).
  Who has the higher years of school completed?
  Was the difference statistically significant?

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One-Way Analysis of Variance

• Now we want to compare means for more than two
  groups.
• Click on Analyze/Compare Means/Means.
• Select the variable that defines your groups by
  clicking on it and moving it to the Independent
  List box. Do this for DEGREE.
• Select the variable that you want to use as your
  comparison variable and move it to the Dependent
  List box. Lets use AGEKDBRN as our comparison
  variable.

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One-Way Analysis of Variance (continued)

• Click on Options to open the Means Options
  box.
• Click in the Anova table and eta box to select
  it and indicate that you want to do a One-Way
  ANOVA.
• Click on Continue and on OK.

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Exercises for One-Way ANOVA

• Use One-Way ANOVA to compare the mean years of
  school completed (EDUC) of respondents who voted
  for Bush, Kerry, and someone else (PRES04).
  Which group had the most education and which had
  the least education? Was the F-value
  statistically significant?
• Compare the number of hours watching television
  (TVHOURS) for people of different levels of
  education (DEGREE). Who watches more television
  those with more education or those with less
  education? Was the F-value statistically
  significant?

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Dummy Variables

• Open the STATES.SAV file.
• Create new variable for whether state is in
  South.
• Click on Transform
• Click on Compute Variable
• Under Target Variable, type SOUTH.
• Under Numeric Expression, type 0.
• Click on OK.

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Dummy Variables (continued)

• Click on Transform
• Click on Compute Variable
• Under Numeric Expression, type 1.
• Click on If
• Click on Include if case satisfies condition.
• In 1st box, type REGION 3.
• Click on Continue and OK.
• When asked if you want to Change exiting
  variable?, click on OK.

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Dummy variables (continued)

• Create new variable called WEST that is 1 if
  REGION equals 4, 0 otherwise. Note be sure to
  click on Reset in the Compute Variable dialog box
  before proceeding further.

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Correlation and Regression(see chs. 7 and 8 in
text)

• Click on Analyze gt Correlate gt Bivariate.
• Select PID, IDEO, MARRIED, and SOUTH and WEST
• Click on one-tailed and on OK.

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Correlation and Regression(continued)

• Click on Analyze gt Regression gt Linear.
• Select PID, as the dependent variable, and IDEO,
  MARRIED, SOUTH and WEST as independent
  variables.
• Click on OK.

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Exercises for Correlation and Regression

• Open the GSS06A file. Create a correlation
  matrix among the following EDUC, MAEDUC, PAEDUC,
  PRESTG80, and SEI.
• Open the STATES file. What explains variation
  among states in propensity toward charitable
  giving (CHARITY)?

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Charts/Graphs(see ch. 9 in text)

• Pie charts
• Bar charts
• Histograms
• Boxplots
• Scatterplots

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General Information About Graphs

• There are three ways to produce charts in SPSS
• Chart Builder
• Legacy
• Classical
• Interactive
• Well be using the last of these

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Simple Pie Charts

• Select Graphs gt Legacy Dialogs gt Interactive gt
  Pie gt Simple.
• Move DEGREE into first box on right.
• Move PCT into second box on right.
• Click on OK.

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Editing the Pie Chart

• Double click anywhere inside the pie chart to
  open the Chart Editor.
• Click Options gt Title, and add a title to your
  chart.
• Click Options gt Hide Legend.
• Click Elements gt Show Data Labels to display
  percents and data labels.
• Click Elements gt Explode Slice.

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Copying the Pie Chart

• Close the Chart Editor
• Select the pie chart by single clicking on it.
• Click on Edit and then on Copy.
• Go to your report in Word and click on Edit gt
  Paste Special gt JPEG gt OK.

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Simple Bar Charts

• Select Graphs gt Legacy Dialogs gt Interactive gt
  Bar
• Move PCT into first box on right.
• Move DEGREE into second box on right.
• Click on OK.

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Clustered Bar Chart

• Select Graphs gt Legacy Dialogs gt Interactive gt
  Bar
• Move PCT into first box on right.
• Move DEGREE into second box on right.
• Move SEX into third box on right.
• Click on OK.

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Histogram

• Select Graphs gt Legacy Dialogs gt Interactive gt
  Histogram
• Move PCT into first box on right.
• Move AGE into second box on right.
• In Histogram tab, check box for Normal curve.
• Click on OK.

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Boxplot for Single Variables

• Open the STATES.SAV file.
• Select Graphs gt Legacy Dialogs gt Interactive gt
  Boxplot
• Move MEDIANHS into first box on right.
• Move STATE into last box on right.
• Click on OK.

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Boxplot by Categories of a Second Variable

• Select Graphs gt Legacy Dialogs gt Interactive gt
  Boxplot
• Move MEDIANHS into first box on right.
• Move REGION into second box on right.
• Move STATE into last box on right.
• Click on OK.

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Scatterplots

• Select Graphs gt Legacy Dialogs gt Interactive gt
  Scatterplot.
• In Assign Variables tab
• move PID into 1st box.
• move IDEO into 2nd box.
• move REGION into 4th box.
• move STATE into last box

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Scatterplots (continued)

• In Fit tab
• Under Method, select Regression.
• Click on OK.

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Exercises for Graphs

• Using GSS06A.SAV
• Create a pie chart and a bar chart for POLVIEWS.
• Create a histogram for SEI.
• Create a boxplot for SEI and then create separate
  boxplots for males and females.
• Using STATES.SAV, create a scatterplot for
  TRAFFIC and URBAN.
• Try various ways of editing your graphs.
• Copy the graphs into Word.

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Where do you go from here?

• Explore the help menu.
• Spend some time playing with SPSS.
• Try out different ways of analyzing your data.
• Show them to others for suggestions.

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Upcoming Workshops

• Intermediate SPSS February 13
• Social Science Data Bases April 24
• Survey Documentation and
• Analysis (SDA) May 15

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Social Science Data Bases April 24

• Subscription Data Bases
• Inter-University Consortium for Political and
  Social Research
• Field Polls
• Roper Polls
• Publicly Available Data
• Teaching with Data
• SSRIC Teaching Resources
• Other Teaching Resources

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Survey Documentation and Analysis (SDA) May 15

• What is online analysis?
• Available SDA data sets
• Codebooks
• Statistical procedures (Frequencies, Crosstabs,
  Regression)
• Recoding, subsetting, downloading
• Teaching resources for SDA

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Feedback?

• Please fill out an evaluation form.
• Thanks!