IBM SPSS Step-by-Step Guide: Correlations.
U5D1- Correlation Versus Causation
• If correlation does not imply causation, what does it imply?
• Are there ever any circumstances when a correlation can be interpreted as evidence for a causal connection between two variables?
• If yes, what circumstances?
To successfully complete this learning unit, you will be expected to:
1. Analyze the interpretation of correlation coefficients.
2. Identify the assumptions of correlation.
3. Identify null hypothesis testing of correlation.
4. Interpret a correlation reported in the scientific literature.
5. Analyze the assumptions of correlation.
Unit 5 Study 1
Use your Warner text, Applied Statistics: From Bivariate Through Multivariate Techniques , to complete the following:
• Read Chapter 7, “Bivariate Pearson Correlation,” pages 261–314. This chapter addresses the following topics:
◦ Assumptions of Pearson’s r.
◦ Preliminary data screening for Pearson’s r.
◦ Statistical significance tests for Pearson’s r.
◦ Factors influencing the magnitude and sign of Pearson’s r.
◦ Effect-size indexes.
◦ Interpretation of Pearson’s r values.
• Read Chapter 8, “Alternative Correlation Coefficients,” pages 315–343. This chapter addresses the following topics:
◦ Correlations for rank or ordinal scores.
◦ Correlations for true dichotomies.
◦ Correlations for artificial dichotomies.
◦ Chi-square test of association.
Walk, M., & Rupp, A. (2010). Pearson product-moment correlation coefficient. In N. J. Salkind (Ed.), Encyclopedia of research design (pp. 1023–1026). Thousand Oaks, CA: Sage. doi:10.4135/9781412961288.n309