Case Q-Q

CO-4: Distinguish among different measurement scales, choose the appropriate descriptive and inferential statistical methods based on these distinctions, and interpret the results.
LO 4.20: Classify a data analysis situation involving two variables according to the “role-type classification.”
LO 4.21: For a data analysis situation involving two variables, determine the appropriate graphical display(s) and/or numerical measures(s) that should be used to summarize the data.
Video: Case Q-Q (2:30)

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Introduction – Two Quantitative Variables

Here again is the role-type classification table for framing our discussion about the relationship between two variables:

It is possible for any type of explanatory variable to be paired with any type of response variable. The possible pairings are: Categorical Explanatory → Categorical Response (C→C), Categorical Explanatory → Quantitative Response (C→Q), Quantitative Explanatory → Categorical Response (Q→C), and Quantitative Explanatory → Quantitative Response (Q→Q). In this section we will be working on Q→Q

Before reading further, try this interactive online data analysis applet.

Interactive Applet: Case Q-Q  

We are done with cases C→Q and C→C, and now we will move on to case Q→Q, where we examine the relationship between two quantitative variables.

In this section we will discuss scatterplots, which are the appropriate visual display in this case along with numerical methods for linear relationships including correlation and linear regression.