1. Correlation

2. Introduction Two meanings of correlation –Research design –Statistical Relationship –Scatterplots

8. Relationship –Scatterplots Quantification of relationship –Correlation coefficient range +1.0 to - 1.0

9. r =.20

10. r =.50

11. r =.80

12. r = -.10

13. r = -.60

14. r = -.90

15. Pearson Product Moment Correlation

22. Relationship –Scatterplots Quantification of relationship –Correlation coefficient range +1.0 to - 1.0 –Pearson Product Moment Correlation

23. Covariance

24. Assumptions when using Pearson: 1.The relationship is linear. 2.The scale of measurement is interval or ratio 3.That there is a bivariate normal distribution - X and Y scores are normally distributed in the population. 4.Homogeneity of variance - at each X score Y scores in the population are normally distributed and vice versa.

25. Significance of correlations

28. Interpreting correlations r2r2 –proportional reduction in error

29. Effect size and Power Cohen –.10 small effect size –.30 medium effect size –.50 large effect size To get power of.80, number of participants required are: –783 for small effect size – 85 for medium effect size – 28for large effect size

30. Potential Problems 1.Correlation and causality 2.Restricted range 3.Outliers.

31. Alternative Correlational Techniques Point - biserial coefficient r pb The Phi coefficient - φ Spearman Rank Order Correlation