STATISTICS

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STATISTICS

• Choosing among statistics
• 1. number of independent variables
• 2. level of measurement (nominal to ratio)
• 3. number of dependent variables
• 4. level of measurement (nominal to ratio)
• 5. other considerations (normality)

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Example
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Statistical analysis

• Cross-tabulation
• 1 Independent variable (categorical)
• 1 Dependent variable (categorical)
• Example percentages by group
• 70 of men
• 50 of women

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Crosstabs

• Covariation
• one categorical independent variable
• e.g., male or female
• one categorical dependent variable
• e.g., blonde, not blonde
• 10 of males are blonde, 40 of females
• significant covariation?

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Two approaches

• How do you measure the covariation?
• 1. inter-ocular test
• does it hit you between the eyes?
• does it look big?

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Crosstabs

• 2. Statistics (exact probability)
• calculate the difference between
• observed rates
• expected rates (chance)
• if observed is different than chance,
• non-independence between variables

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Crosstabs

• OBSERVED
• Blonde Not TOTAL
• Male 10 90 100
• Female 40 60 100
• TOTAL 50 150 200

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Chi-square Test statistic

• Calculate Chi-square
• Sum of (Observed-Expected) 2
• Expected
• do this for each cell

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Chi-square Calculation

• Blonde Not TOTAL
• Male 10 90 100
• 25 75
• 9 3 12
• Female 40 60 100
• 25 75
• 9 3 12
• TOTAL 50 150 200
• 24

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Chi-square Test statistic

• 2. Interpret result
• to X2 w/ (k-1)(n-1) degrees of freedom
• (Table X2 1 d.f. p lt .05 3.84)
• Because X2 obs 24 gt 3.84,
• REJECT Ho

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SPSS Output
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SPSS Output
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SPSS Output
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SPSS Output
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SPSS Output
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SPSS Output
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The End