AP Stats Chapter 3: Regression and Residuals
Textbook Sections to read
3.1 pg. 141-157
Explanatory and response
variables
Displaying relationships:
Scatterplots
Interpreting scatterplots
Technology: Scatterplots on
the calculator
Measuring linear association:
correlation
Facts about correlation
3.2 pg. 164-173
Least-squares regression
Interpreting a regression line
Prediction
Technology: Least-squares
regression lines on the
calculator
Residuals and the leastsquares regression line
Calculating the equation of
the least-squares regression
line
Technology: Residual Plots
and s on the Calculator
3.2 pg. 174-181
How well the line fits the
data: residual plots
How well the line fits the
data: the role of r2 in
regression
Name____________________
I can…
Assignment
(1, 5, 7, 11,
 Describe why it is important to investigate
13-17, 26-32)
relationships between variables.
 Identify explanatory and response variables
in situations where one variable helps to
explain or influences the other.
 Make 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 in
context.
 Explain how the correlation r is influenced
by extreme observations.












Interpret the slope and y-intercept of a leastsquares regression line in context.
Explain the concept of least squares.
Use technology to find a least-squares
regression line.
Fond the slope and intercept of the leastsquares regression line from the means and
standard deviations of x and y and their
correlation.
Calculate and interpret residuals in context.
Explain the concept of least squares.
Use technology to find a least-squares
regression line.
Find the slope and intercept of the leastsquares regression line from the means and
standard deviations of x and y and their
correlation.
Pg. 191 (35,
39, 41, 45, 47,
53)
Construct and interpret residual plots to
assess if a linear model is appropriate.
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.
Pg. 192 (49,
54, 56, 58-61)
3.2 pg. 181-190
Intepreting computer
regression output

Correlation and regression
wisdom


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.
Technology: Least-squares
regression using minitab and
JMP
Ch 3 Review
Ch 3 Test
Free Response:
1998 #2 histogram and scatterplot
1998 #4 regression output and residual plot
1999 #1 residual plot, slope and y-intercept from computer output
1000 #1 describing scatterplots
2002 #4 regression output, correlation from computer output
2002B #1 scatterplot, correlation, r squared
2003B #1 influential points
2005 #3 residual plots, interpreting slope and r squared
2007B #4 graphing least-squares regression, residual, influential points
Pg. 194 (63,
65, 69, 71-78)
Ch 3 Review
Ch 3 Test
2005 #3
3.1
 Describe why it is
important to investigate
relationships between
variables.
 Identify explanatory
and response variables
in situations where one
variable helps to explain
or influences the other.
 Make 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 in
context.
 Explain how the
correlation r is
influenced by extreme
observations.
3.2 part I
 Interpret the slope and
y-intercept of a leastsquares regression line
in context.
 Explain the concept of
least squares.
 Use technology to
find a least-squares
regression line.
 Find the slope and
intercept of the leastsquares regression line
from the means and
standard deviations of x
and y and their
correlation.
 Calculate and
interpret residuals in
context.
 Explain the concept of
least squares.
 Use technology to
find a least-squares
regression line.
 Find the slope and
intercept of the leastsquares regression line
from means & standard
deviations of x and y &
their correlation.
3.2 part II
 Construct and
interpret residual plots
to assess if a linear
model is appropriate.
 Use the standard
deviation of the
residuals to assess how
well the line fits the
data.
 Use r to assess how
well the line fits the
data.
 Interpret the standard
deviation of the
2
residuals and r in
context.
2
3.2 part III
 Identify equation of
least-squares regression
from computer output.
 Explain- association
doesn’t imply causation.
 Recognize how slope,
y intercept, standard
deviation of residuals,
2
and r are influenced by
extreme observations.