Work through the list without notes. If you cannot do a statement, follow its link, then come back. Guide = study guide; Practice = practice questions.
Understanding
- I can explain what bivariate quantitative data are and why both values must come from the same individual. (Guide: “From one variable to two”)
- I can explain the difference between an explanatory and a response variable, and why “explanatory” does not mean “cause”. (Guide: “Explanatory and response variables”; Practice Q1)
- I can explain what a positive or a negative association means, using “tends to”. (Guide: “Describing a scatterplot: four features”; Practice Q2)
- I can explain why strength depends on scatter around the pattern, not on steepness. (Guide: “Describing a scatterplot: four features”; Practice Q3, Q7)
Skills
- I can choose which variable goes on each axis in a new context. (Guide: “Explanatory and response variables”; Practice Q1, Q4)
- I can construct a scatterplot with labelled axes, units and equal scale steps, without joining the dots. (Guide: “Constructing a scatterplot”; Practice Q4)
- I can describe the form, direction and strength of an association, including a curved one. (Guide: Worked examples 1 and 2; Practice Q4, Q7)
- I can identify unusual points and clusters and suggest a reason for them in context. (Guide: Worked example 1; Practice Q5)
Reasoning
- I can use a scatterplot to decide whether a claim is supported, quoting evidence from the data. (Guide: Worked example 3; Practice Q6)
- I can use one counterexample to reject a claim that says “always” or “every”. (Guide: Worked example 3; Practice Q6)
- I can explain why an association shown in a scatterplot does not on its own show that one variable causes changes in the other. (Guide: Worked example 3)
- I can write every description in context, naming both variables and the individuals. (All worked examples)
All ticked? Move on to Topic 5.2: Correlation, or return to the course roadmap.