Lecture notes with Experimental and Correlational Research at the Leiden University - 2018/2019
Lecture 1
6/2/2019
-Correlation is about two variables being associated, but there is no evidence of causality.
-Causality however requires multiple factors: covariance (variables have an association), directionality(cause precedes effect (in time)) and internal validity(eliminate alternative explanations).
- Correlations can be displayed in scatterplots that show:
- Direction: positive or negative
- Strength: density of the points
- Shape: linear/nonlinear and homogeneous (one cluster) / heterogeneous (multiple clusters).
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