Unit 2 Review

1. Unit 2 Review

2. Review of Chapter Objectives • Sec 3.1: Scatterplots • Given a 2 variable data set, construct and interpret a scatterplot. • Identify which of two variables is explanatory and which is responsive. • Describe a scatterplot in terms of direction, shape and strength. • Construct and interpret a scatterplot with 3 variables, one of which is categorical.

3. Review of Chapter Objectives • Sec 3.2: Correlation • Calculate the Correlation Constant r from linear models by using a formula and on calculator. • Use the Correlation Constant r to describe strength and direction of a relation.

4. Review of Chapter Objectives • Sec 3.3: Least Squares Regression • Find the Least Squares Regression Line (LSLR) by using formulas and calculator. • Create a Residual Plot on calculator and draw conclusions about goodness of fit of LSLR. • Use LSLR to predict y for a given x. • Describe how outliers and influential observations affect LSLR. • Use r-squared to describe how much of the y-variation comes from the linear relation with x

5. Review of Chapter Objectives • Sec 4.1: Modeling nonlinear data • Given a data set that grows exponentially, use transformations to find its equation. • Given a data set that behaves like a polynomial, use transformations to find its equation. • Determine from problem context and residual plots whether the exponential or polynomial model gives the best fit of the data.

6. Review of Chapter Objectives • Sec 4.2: Interpreting Correlation and Regression • Interpret regression in light of extrapolation limitations, “lurking” variables, and the issue of association vs. causation. • Sec 4.3: Relations in Categorical Data • From a two-way table of counts, find the marginal distributions of both variables. • Express conditional distributions as percents. • Describe the relationship between two categorical variables by comparing percents.