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Chapters 3 and 4 — Correlation and Least-Squares Regression

In this unit, students analyze bivariate quantitative data to describe the relationship between two numerical variables. They learn to represent these relationships using scatterplots and describe them in terms of direction, form, strength, and unusual features (such as outliers or clusters).

Students will calculate and interpret the correlation r to quantify the strength and direction of a linear association. They will also determine the Least-Squares Regression Line (LSRL) to model linear data and use the equation (ŷ = a + bx) to make predictions.

By analyzing residuals, the residual plot, and the coefficient of determination r2, students will assess the appropriateness of a linear model. Finally, they will learn to interpret the slope and y-intercept in the context of the data, providing a foundation for inference for slope later in the course.


PPractice Exam for Bivariate Data

Quick self-checks and formative quizzes.