Survey research and design in psychology/Lectures/Correlation
Jump to navigation
Jump to search
Lecture 4: Correlation
Resource type: this resource contains a lecture or lecture notes. |
This is the fourth lecture for the Survey research and design in psychology unit of study.
This page is complete for 2018. |
Outline[edit]
This lecture overviews non-parametric and parametric approaches to (bivariate) measures of association (dependence), i.e., correlational statistics and graphing. The lecture is accompanied by a computer-based tutorial.
This lecture explains:
- The purpose of correlation (what types of question(s) are we trying to answer?)
- Nature of covariation (what does it mean if two variables covary or “vary together”?)
- Correlational analyses
- Types of answers – What can we conclude?
- Types of correlation – Selecting appropriate correlations and graphs based on the variables' level of measurement
- Interpretation – of correlational relations and graphs
- Assumptions and Limitations
- Dealing with several correlations
Slides[edit]
- Lecture slides (Google Slides]
- 2018 handouts:
Readings[edit]
- Howitt and Cramer (2014a):
- Chapter 07: Relationships between two or more variables: Diagrams and tables (pp. 86-97
- Chapter 08: Correlation coefficients: Pearson correlation and Spearman’s rho (pp. 98-119)
- Chapter 11: Statistical significance for the correlation coefficient: A practical introduction to statistical inference (pp. 143-156)
- Chapter 15: Chi-square: Differences between samples of frequency data (pp. 196-217)
See also[edit]
- Descriptives & graphing (Previous lecture)
- Exploratory factor analysis (Next lecture)
- Correlation (Tutorial)
- Correlation
- Correlation quiz (Practice)
External links[edit]
- Relationships between two or more variables: Diagrams (Ch 9) Quiz (Practice) (Howitt & Cramer, 2014)
- Correlation co-efficients (Ch 10) Quiz (Practice) (Howitt & Cramer, 2014)