Name ___________________________
Chapter 3 Syllabus - AP Statistics - A
Describing Relationships
Chapter Objective: Students will study the importance of relationships between quantitative variables, use
scatterplots to display the relationship, and describe the relationship using correlation, linear association, and a leastsquares regression model.
Day 1
9/27
TOPICS:
▪Explanatory
and response
variables
▪Scatterplots
▪Correlation
Day 2
10/1
TOPICS:
▪Scatterplots
▪Correlation
▪Interpret a
regression
line
▪Making
Predictions
▪Extrapolation
Introduction – Chapter 3 Project
3.1 – Scatterplots and Correlation
Concepts and Skills to Master: ►Identify explanatory and response variables in
situations where one variable helps explain or influences the other ►Construct a
scatterplot to display the relationship between two quantitative variables
►Describe the direction, form, and strength of the overall pattern of a scatterplot
►Recognize outliers in a scatterplot ►Know the basic properties of correlation
►Calculate and interpret correlation ►Explain how the correlation r is
influenced by extreme observations
II. Assignments
A. Warm Up
B. Chapter 3 Project; due ___OCT. 8th ___
C. CYU p.144, 149, 154
D. Technology Lab: Scatterplots and Correlation
III. Homework
A. Reading Guide 3.1
B. Pages 158-159 #2, #6, #7, #11, #14
I.
3.1 – Scatterplots and Correlation
3.2 – Least Squares Regression
I. Concepts and Skills to Master: ►Know the basic properties of correlation
►Calculate and interpret correlation ►Explain how the correlation r is
influenced by extreme observations ►Interpret the slope and y intercept of a leastsquares regression line in context. ►Use the least-squares regression line to predict y
for a given x ►Explain the dangers of extrapolation
II. Assignments
A. Warm Up
B. Homework Q & A
C. Chapter 3 Project
D. Classwork – 3.1 Quiz handout
I. Homework
A. Textbook: pages 160-162 #14 – 18, #21, #26
B. Reading Guide 3.2
C. Chapter 3 Project
Syllabus continued on back…
Essential Questions To Answer
1.
2.
3.
4.
What is a relationship between two or more variables? How can we examine it?
What type of variables impact association studies? How are they displayed?
Where are the individuals in a graphical representation of bivariate data?
What is the difference between independent and dependent variables and explanatory and response variables?
5. What are confounding (‘lurking’) and other variables?
6. If the overall pattern of a bivariate observation is regular, how can we describe it by a smooth curve that is a
mathematical model?
7. Why are residual plots used to determine linearity in the association of bivariate data?
8. What is the distinction between association and causation?
9. What is the distinction between association and independence?
Day 3
10/3
TOPICS:
▪Residuals
and the LeastSquares
Regression
Line
▪Calculating
the Equation
of the LeastSquares
Regression
Line
▪Computer
Regression
Output
▪Residual
Plots
Day 4
10/5
QUIZ
3.2 – Least-Squares Regression
I. Concepts and Skills to Master: ►Calculate the equation for the least squares
regression line ►Calculate and interpret residuals in context ►Explain the concept of
least squares ►Find the slope and intercept of the least squares regression line from the
means and standard deviations of x and y and their correlation ►Construct and interpret
residual plots to assess if a linear model is appropriate
II. Assignments
A. Warm Up
B. Homework Q & A
C. Technology Lab
D. Classwork – pages 162-163 #27-32
III. Homework
A. Chapter 3 Project
B. Textbook: pages 191-192 #36, 38, 40, 43, 45, 47, 53
C. Chapter 3 Take Home Quiz - Study for Quiz
3.2 Least Squares Regression
I. Concepts and Skills to Master: ►Use the standard deviation of the residuals to assess
how well the line fits the data ►Use r2 to assess how well the line fits the data ►Interpret the
standard deviation of the residuals and r2 in context ►Identify the equation of a least squares
regression line from computer output ►Explain why association doesn’t imply causation
Recognize how the slope, y intercept, standard deviation of the residuals, and r2 are influenced by
extreme observations
I. Assignments
A. HW Q & A
B. Class Discussion – Concepts and Skills To Master
C. Guided Notes
D. Quiz
II. Homework
A. Textbook: pages 192-197 #49, 54, 58-61, 71-78
B. Complete Chapter 3 Project
TEST
Chapters 1- 4 Test
PROJECT : Due Tuesday, Oct. 9th
Monday – 10.15.2012
Chapter 3 Vocabulary
Coefficient of Determination
Correlation r (correlation coefficient)
Influential Observations
Least Squares Regression Line
Residual plot
Direction
Extrapolation
Linear
Regression Line
Response Variable
Explanatory Variable
Form and Strength
Negative and Positive Association
Residual
Scatterplots