Data analysis: two variables

Practice 5 items →

Two variables: the line is a model and the residuals say whether it was honest. Students read two-way tables, describe scatter plots, fit and interpret a line, interpret r, read a residual plot, and refuse to confuse correlation with causation.

Specification · for a parent or teacher

Part no.: bivariate-regression
Course: High School Math 1 · Unit 18
Realm: Applied
Difficulty: 4 of 4 — Grade 7 / Math 1 core. Structure, models, proofs on the grid.
Qty: 5 items

Part no. is the node's id; the realm is the kind of math; qty is how many practice items it carries.

Students can

build and read a two-way table (joint, marginal, conditional); describe a scatter; fit a line by technology and interpret slope and intercept in context; interpret $r$ ; read a residual plot.

Ready when

given a scatter and a residual plot, they say whether a linear model is appropriate and interpret $r=-0.8$ in context.

Formulas

Residual

e = y - \hat y

Correlation range

-1 \le r \le 1

Watch for

$r=0.2$ called “strong”; residual plot ignored; “ice cream causes drowning” from a summer scatter.

Before · requires

Statistics: center and spreaddescriptive-stats-spread · Math 1
Linear equations and inequalities (two variables)linear-forms-half-planes · Math 1

After · used by

— none

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