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Understanding Measures and Variables in Statistics: Nominal, Ordinal, and Interval Types

This review summarizes the types of measures and variables commonly used in statistics, focusing on nominal, ordinal, and interval scales. Nominal examples include gender, major, blood type, and eye color, while ordinal includes rank-order of favorite films and Likert scales. The review also discusses main analysis techniques using SPSS, such as cross-tabulation with Chi-Square, t-tests, and ANOVA, along with interpreting outputs like means, p-values, and variance. Emphasis is placed on regression analysis and the significance of correlation in understanding data relationships.

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Understanding Measures and Variables in Statistics: Nominal, Ordinal, and Interval Types

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  1. Statistics & SPSS Review Fall 2009

  2. Types of Measures / Variables • Nominal / categorical • Gender, major, blood type, eye color • Ordinal • Rank-order of favorite films; Likert scales? • Interval / scale • Time, money, age, GPA

  3. Main Analysis Techniques

  4. Main Analysis Techniques

  5. SPSS Cross –tab with Chi-Square

  6. SPSS Cross –tab with Chi-Square p < .05

  7. Main Analysis Techniques

  8. SPSS t-test Output

  9. SPSS t-test Output 1. Read means 3. Read p value 2. Read Levene’s Test

  10. Analysis of Variance

  11. SPSS ANOVA output

  12. SPSS ANOVA output p value

  13. Variables & Statistical Tests

  14. Variance  x i - Mean )2 Variance = s2 = ----------------------- N Standard Deviation = s =  variance

  15. Regression line W = 3.3 H - 73

  16. Scatterplot: Sentence by G.P.A.

  17. Regression Coefficients Sentence = -3.5 G.P.A. + 18

  18. Correlation

  19. Correlation: Sentence & G.P.A.

  20. Correlation: Sentence & G.P.A. p value

  21. Correlation Interpreting r as r2 r = -.22 r2 = .05 G.P.A. “explains” 5% of variance in SENTENCE length

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