 ## Cramming Sam's top tips from chapter 8

Click on the topic to read Sam's tips from the book

### Correlation

• A crude measure of the relationship between variables is the covariance.
• If we standardize this value we get Pearson’s correlation coefficient, r.
• The correlation coefficient has to lie between −1 and +1.
• A coefficient of +1 indicates a perfect positive relationship, a coefficient of −1 indicates a perfect negative relationship, and a coefficient of 0 indicates no linear relationship.
• The correlation coefficient is a commonly used measure of the size of an effect: values of ±0.1 represent a small effect, ±0.3 is a medium effect and ±0.5 is a large effect. However, interpret the size of correlation within the context of the research you’ve done rather than blindly following these benchmarks.

### Correlations

• Spearman’s correlation coefficient, rs, is a non-parametric statistic and requires only ordinal data for both variables.
• Kendall’s correlation coefficient, τ, is like Spearman’s rs but probably better for small samples.
• The point-biserial correlation coefficient, rpb, quantifies the relationship between a continuous variable and a variable that is a discrete dichotomy (e.g., there is no continuum underlying the two categories, such as dead or alive).
• The biserial correlation coefficient, rb, quantifies the relationship between a continuous variable and a variable that is a continuous dichotomy (e.g., there is a continuum underlying the two categories, such as passing or failing an exam).

### Partial and semi-partial correlations

• A partial correlation quantifies the relationship between two variables while accounting for the effects of a third variable on both variables in the original correlation.
• A semi-partial correlation quantifies the relationship between two variables while accounting for the effects of a third variable on only one of the variables in the original correlation.