Introduction to SPSS

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Introduction to SPSS

• Graphing/t Test Procedures

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Graphing

• Bar
• Simple vs. Clustered
• 1 IV vs. multiple IVs
• Bars Represent y-axis
• of Cases (in each group)
• Cumulative Num of Cases
• of Cases
• Cumulative of Cases
• Other Summary Function (default is mean)
• Change Summary to use stat other than mean
• Category Axis x-axis

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Bar Chart
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Line Chart

• Line
• Basically, same as Bar
• More accurate if IV groups form continuum
  (polychotomized artificially)
• Simple vs. Multiple
• Same as Simple vs. Clustered

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Line Chart
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Area Chart

• Area
• Same as Line and Bar

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Pie Chart

• Pie
• Summaries for Groups of Cases
• Choose one discrete variable (with multiple
  groups)
• Same as Bar, Line, Area charts
• Summaries of Separate Variables
• Choose several dimensional variables (without
  subgroups) and SPSS combines them for you
• Values of Individual Cases
• Dont worry about this one

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Pie Chart
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Boxplot

• Boxplot
• Simple vs. Clustered

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Histogram

• Histogram
• Really just a bar chart that displays Num of
  Cases only
• Click Display Normal Curve to inspect if your
  distribution deviates from normal

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One-Sample t Test

• Tests for difference between sample mean and
  pre-determined population mean
• Click Analyze ? Compare Means ? One- Sample
  T Test
• Test Value Predetermined population mean
• Options
• Exclude Cases Listwise If multiple variables
  used, only use cases that have values on ALL
  variables
• Exclude Cases Analysis by Analysis

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One-Sample T Test
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Paired-Samples t Test

• Tests if two related samples differ significantly
  from one another
• Click Analyze ? Compare Means ?
  Paired-Samples T Test

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Paired-Samples t Test
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Independent-Samples t Test

• Tests if two unrelated samples differ
  significantly from one another
• Click Analyze ? Compare Means ?
  Independent-Samples T Test
• Test Variable(s) DV
• Grouping Variable IV
• Click Define Groups
• MergeFile1.sav Male 1 Female 0
• If IV dimensional, can use cut point to create
  groups i.e. x gt 7 Grp 1, x 7 Grp 2
• Levenes Test for Equality of Variances
• If significant, equal variances cannot be assumed

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Independent-Samples t Test