- Construct and interpret a boxplot and side-by-side boxplots
- Use the IQR method to identify outliers
- Construct and interpret histograms with groups and dotplots with groups
- Construct and interpret a scatterplot
- Compute and interpret a correlation
- Construct and interpret a simple linear regression model (i.e., one explanatory and one response variable)
- Compute and interpret residuals from a simple linear regression model
- Interpret plots of more than two variables
- Select an appropriate graphical representation for a given scenario
In Lessons 2 and Lesson 3 you learned about describing data. We have stressed the importance of being able to distinguish between categorical and quantitative variables. The summary statistics that you compute and the visual representations that you create are dependent on the number and types of variables that you are working with.
Before moving on to Lesson 4, you should check your understanding of the learning objectives above and review the objectives from Lessons 1 and Lesson 2 as well. These first three lessons will serve as a foundation for the rest of the course.