Are there ever any circumstances when a correlation can be


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?

OBJECTIVES

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.

Readings

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

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