Lecture slides stats1.13.l24.air

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Lecture slides stats1.13.l24.air

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  • 1. Statistics One Lecture 24 Course Summary 1
  • 2. Four segments •  Research methods and descriptive statistics  –  Lectures 1 – 6 •  Simple and multiple regression –  Lectures 7 – 14 2
  • 3. Four segments •  Group comparisons with t-tests and ANOVA  –  Lectures 15 – 18 •  Procedures for non-normal distributions and non-linear models –  Lectures 19 – 23 3
  • 4. Lecture 24 ~ Segment 1 Research Methods and Descriptive Statistics 4
  • 5. Research methods •  Descriptive research •  Experimental research •  Correlational research
  • 6. Descriptive statistics •  Histograms •  Summary statistics •  Measures of central tendency •  Mean •  Median •  Mode •  Measures of variability •  Standard deviation •  Variance
  • 7. Descriptive statistics •  Correlation •  Covariance •  Scatterplots
  • 8. Descriptive statistics •  Measurement •  Classical true score theory •  Reliability •  Validity
  • 9. END SEGMENT 9
  • 10. Lecture 24 ~ Segment 2 Simple and multiple regression 10
  • 11. Simple and multiple regression •  Simple regression equation has only one predictor variable (X) •  Multiple regression equation has multiple predictor variables
  • 12. NHST •  NHST can be used to test statistical significance of individual predictor variables and to test statistical significance of the model
  • 13. NHST •  •  •  •  •  •  Sampling Sampling error Sampling distribution Central limit theorem Problems with NHST Remedies
  • 14. NHST •  Problems with NHST •  •  •  •  •  •  BAYES Biased by sample size Arbitrary decision rule Yokel local test Error prone Shady logic
  • 15. NHST •  Remedies •  •  •  •  •  Effect size Confidence intervals Model comparison Replications Power
  • 16. Simple regression •  Regression equation •  Regression constant •  Regression coefficient (unstandardized and standardized) •  Residual •  Ordinary Least Squares
  • 17. Mutiple regression •  •  •  •  •  •  Matrix algebra Regression equation (model) Regression constant Regression coefficients (unstandardized and standardized) Residual Model comparison •  Ordinary Least Squares
  • 18. Mutiple regression •  Moderation •  Dummy coding •  Centering •  Mediation •  Sobel test
  • 19. END SEGMENT 19
  • 20. Lecture 24 ~ Segment 3 Group Comparisons t-tests and ANOVA 20
  • 21. Group comparisons •  z-test •  Single sample t-test •  Independent t-test –  Homogeneity of variance assumption –  Levene’s test •  Dependent t-test (paired samples)
  • 22. Group comparisons •  ANOVA: One-way between groups –  F = MSA = MSS/A –  Homogeneity of variance assumption –  Levene’s test –  Post-hoc tests
  • 23. Group comparisons •  Factorial ANOVA –  Main effects –  Interaction effect –  Simple effects •  Homogeneity of variance assumption •  Levene’s test •  Post-hoc tests
  • 24. Group comparisons •  Repeated measures ANOVA –  F = MSA = MSAxS –  Sphericity assumption –  Mauchly’s test –  Post-hoc tests
  • 25. END SEGMENT 25
  • 26. Lecture 24 ~ Segment 4 Procedures for non-normal distributions and non-linear models 26
  • 27. Categorical outcome variables •  Chi-square tests •  Logistic regression
  • 28. Non-normal distributions •  How to detect non-normal distributions –  Histograms and scatterplots –  Q-Q plots •  Common transformations –  Square root –  Logarithmic –  Inverse
  • 29. Non-parametric statistics •  Wilcoxan’s ranking method •  Mann-Whitney U
  • 30. Non-linear models •  Generalized Linear Model –  Binomial –  Multinomial –  Poisson
  • 31. END SEGMENT 31
  • 32. END LECTURE 24 32