AP Statistics (Period 3) Assignments

Day

Topics

Objectives: Students will be able to …

Suggested homework

1

Chapter 3 Introduction

Activity: CSI Stats

3.1 Explanatory and response variables

3.1 Displaying relationships: scatterplots

3.1 Interpreting scatterplots

• 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.

1, 5, 7, 11, 13

2

3.1 Measuring linear association: correlation

3.1 Facts about correlation

• Know the basic properties of correlation.
• Calculate and interpret correlation.
• Explain how the correlation r is influenced by extreme observations.

14–18, 21, 26

3

3.2 Least-squares regression

3.2 Interpreting a regression line

3.2 Prediction

• Interpret the slope and y intercept of a least-squares regression line.
• Use the least-squares regression line to predict y for a given x.
• Explain the dangers of extrapolation.

27–32,

35, 37, 39, 41

4

3.2 Residuals and the least-squares regression line

3.2 Calculating the equation of the least-squares regression line

• Calculate and interpret residuals.
• Explain the concept of least squares.
• Use technology to find a least-squares regression line.
• Find the slope and intercept of the least-squares regression line from the means and standard deviations of x and y and their correlation.

43, 45, 47, 53

5

3.2 How well the line fits the data: residual plots

3.2 How well the line fits the data: the role of r² in regression

• 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.

49, 54, 56, 58–61

6

3.2 Interpreting computer regression output

3.2 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.

63, 65, 68, 69, 71–78

7

Chapter 3 Review

Chapter Review Exercises

8

Chapter 3 Test

33^R, 34^R, 79^R, 80^R, 81^R

Day

Topics

Objectives: Students will be able to…

Suggested Homework

1

2.1 Introduction, Measuring Position: Percentiles, Cumulative Relative Frequency Graphs, Measuring Position: z-scores

• Use percentiles to locate individual values within distributions of data.
• Interpret a cumulative relative frequency graph.
• Find the standardized value (z-score) of an observation. Interpret z-scores in context.

5, 7, 9, 11, 13, 15

2

2.1 Transforming Data, Density Curves

• Describe the effect of adding, subtracting, multiplying by, or dividing by a constant on the shape, center, and spread of a distribution of data.
• Approximately locate the median (equal-areas point) and the mean (balance point) on a density curve.

19, 21, 23, 31, 33-38

3

2.2 Normal Distributions, The 68-95-99.7 Rule, The Standard Normal Distribution

• Use the 68–95–99.7 rule to estimate the percent of observations from a Normal distribution that fall in an interval involving points one, two, or three standard deviations on either side of the mean.
• Use the standard Normal distribution to calculate the proportion of values in a specified interval.
• Use the standard Normal distribution to determine a z-score from a percentile.

41, 43, 45, 47, 49, 51

4

2.2 Normal Distribution Calculations

• Use Table A to find the percentile of a value from any Normal distribution and the value that corresponds to a given percentile.

53, 55, 57, 59

5

2.2 Assessing Normality

• Make an appropriate graph to determine if a distribution is bell-shaped.
• Use the 68-95-99.7 rule to assess Normality of a data set.
• Interpret a Normal probability plot

63, 65, 66, 68, 69-74

6

Chapter 2 Review

Chapter 2 Review Exercises

pgs. 136-138

7

Chapter 2 Test

^{Practice Test pgs. 138-139}