Non-Causal Explanations for Observed Associations is a part of the VCE Further Maths topic Data Analysis. It falls under the subtopic Investigating Associations Between Two Variables. This post looks at non-causal explanations for an observed association including common response, confounding, and coincidence.
- Common response: changes in the dependent and independent variables that results from a change in another variable. This can lead to bias in results or make them invalid.
- Confounding: a variable that influences both the independent and dependent variable. If the confounding variable is not taken into account in an investigation, you might find a correlation that doesn’t really exist.
- Coincidence: inevitable events which occur unpredictably and can alter results.
What is Confounding?
This video looks at the definition of confounding, as well as examples.
https://www.youtube.com/watch?v=sKkCZqqZ3qE
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