# Survey research and design in psychology/Lectures/Correlation

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)