Chapter 3 Syllabus
AP Statistics- Mr. Lee
This Syllabus is subject to change. If you need more practice on a certain type of problem, do the preceding odds problems for the problems listed.
Day / Topics / Class Activities / Suggested homework1 / 3.1 Explanatory and response variables, Displaying relationships: scatterplots, Interpreting scatterplots / · WU: CSI Stats: The case of the missing cookies
· Class data examples for Scatterplots (positive, negative, none)
· DOFS / Read 143 – 149
p. 158: #2, 6, 8, 12
2 / 3.1 Measuring linear association: correlation, Facts about correlation / · WU: Scatterplot
· Correlation example using the definition
· Facts about correlation / Read 150-156
p. 160: #14–18
3 / 3.1 Correlation and How points affect it / · Correlation
· Correlation and Regression Applet
· Calculator Activity/YMS NSpire Exploring Scatterplots / p. 161: #19, 21-23, 26-32
4 / 3.2 Least-squares regression, Interpreting a regression line, Prediction / · Least squares Regression line example / Read 164-167
Do p. 191: #36, 38, 40, 42
5 / 3.2 Calculating the equation of the least-squares regression line / · Calculator steps
· Residuals definition
· Quiz 3.1 / Read 168
p. 191: #39, 41, 45
6 / 3.2 Residuals, Least-squares regression line / · Calculate and interpret residuals.
· Explain the concept of least squares.
· Calculating the least squares line by hand / Read 169-174
p. 191: 44, 46, 47, 48, 54
7 / 3.2 How well the line fits the data: residual plots / · WU: Cost and Width
· Residual Plot Examples
· Standard deviation of the residuals / Read 174-178
p. 193: #56, 59, 60-62
8 / 3.2 How well the line fits the data: the role of r2 in regression, Interpreting computer regression output, Correlation and regression wisdom / · WU: Residual Plots
· R2 example
· Data Exploration: Anscombe’s Data / Read 179-186
p. 192: #48, 50, 52, 54, 58, 64
9 / 3.2 Recognize how the slope, y intercept, standard deviation of the residuals, and r2 are influenced by extreme observations. / · TI Nspire activities Influencing Regression, influential outliers application
· Data Exploration: Notebook Data / Read 187-189
p. 195: #66-68 71–78
10 / Quiz 3.2 / p. 198: #R3.1-R3.4
11 / Chapter 3 Review / Interpretation Review / p. 199: #R3.5-R3.7
12 / Chapter 3 Test