CHAPTER 7
Two-Variable Data Analysis
IN THIS CHAPTER
Summary: In the previous chapter we used exploratory data analysis to help us understand what a one-
variable dataset was saying to us. In this chapter we extend those ideas to consider the relationships
between two variables that might, or might not, be related. In this chapter, and in this course, we are
primarily concerned with variables that have a linear relationship and, for the most part, leave other
types of relationships to more advanced courses. We will spend some time considering nonlinear
relationships that, through some sort of transformation, can be analyzed as though the relationship was
linear. Finally, we’ll consider a statistic that tells the proportion of variability in one variable that can be
attributed to the linear relationship with another variable.
Key Ideas
Scatterplots
Lines of Best Fit
The Correlation Coefficient
Least Squares Regression Line
Coefficient of Determination
Residuals
Outliers and Influential Points
Transformations to Achieve Linearity