Course title

Pre-requisite

Course description

The AP Statistics course is equivalent to a one-semester; introductory; non-calculus-based college course in statistics. The course introduces students to the major concepts and tools for collecting; analyzing; and drawing conclusions from data. Students use technology; investigations; problem solving; and writing as they build conceptual understanding. Students design; administer; and tabulate results from surveys and experiments. Probability and simulations aid students in constructing models for chance behavior. Sampling distributions provide the logical structure for confidence intervals and hypothesis tests. Students use a TI-83/84 or a Casio fx 9750 graphing calculator; Fathom; and Minitab statistical software; and Web-based java applets to investigate statistical concepts. To develop effective statistical communication skills; students are required to prepare frequent written and oral analyses of real data.
Chapter 1
Day Topics Learning Objectives Students will be able to … Suggested assignment
1 Chapter 1 Introduction • Identify the individuals and variables in a set of data.
• Classify variables as categorical or quantitative. 1; 3; 5; 7; 8
1 1.1 Bar Graphs and Pie Charts; Graphs: Good and Bad • Display categorical data with a bar graph. Decide if it would be appropriate to make a pie chart.
• Identify what makes some graphs of categorical data deceptive. 11; 13; 15; 17
2 1.1 Two-Way Tables and Marginal Distributions; Relationships between Categorical Variables: Conditional Distributions • Calculate and display the marginal distribution of a categorical variable from a two-way table.
• Calculate and display the conditional distribution of a categorical variable for a particular value of the other categorical variable in a two-way table.
• Describe the association between two categorical variables by comparing appropriate conditional distributions. 19; 21; 23; 25; 27–32
3 1.2 Dotplots; Describing Shape; Comparing Distributions; Stemplots • Make and interpret dotplots and stemplots of quantitative data.
• Describe the overall pattern (shape; center; and spread) of a distribution and identify any major departures from the pattern (outliers).
• Identify the shape of a distribution from a graph as roughly symmetric or skewed.
• Compare distributions of quantitative data using dotplots or stemplots. 37; 39; 41; 43; 45; 47
3 1.2 Histograms; Using Histograms Wisely • Make and interpret histograms of quantitative data.
• Compare distributions of quantitative data using histograms. 53; 55; 59; 60; 65; 69–74
4 1.3 Measuring Center: Mean and Median; Comparing the Mean and Median; Measuring Spread: Range and IQR; Identifying Outliers; Five-Number Summary and Boxplots • Calculate measures of center (mean; median).
• Calculate and interpret measures of spread (range; IQR).
• Choose the most appropriate measure of center and spread in a given setting.
• Identify outliers using the 1.5×IQR rule.
• Make and interpret boxplots of quantitative data. 79; 81; 83; 87; 89; 91; 93
5 1.3 Measuring Spread: Standard Deviation; Choosing Measures of Center and Spread; Organizing a Statistics Problem • Calculate and interpret measures of spread (standard deviation).
• Choose the most appropriate measure of center and spread in a given setting.
• Use appropriate graphs and numerical summaries to compare distributions of quantitative variables. 95; 97; 99; 103; 105; 107–110
6 Chapter 1 Review/FRAPPY! Chapter 1 Review Exercises
7 Chapter 1 Test
Chapter 2
Day Topics Learning Objectives Students will be able to… Suggested assignment
1 2.1 Measuring Position: Percentiles; Cumulative Relative Frequency Graphs; Measuring Position: z-scores • Find and interpret the percentile of an individual value within a distribution of data.
• Estimate percentiles and individual values using a cumulative relative frequency graph.
• Find and interpret the standardized score (z-score) of an individual value within a distribution of data. 1; 3; 5; 9; 11; 13; 15
2 2.1 Transforming Data • Describe the effect of adding; subtracting; multiplying by; or dividing by a constant on the shape; center; and spread of a distribution of data. 17; 19; 21; 23;
25–30
3 2.2 Density Curves; The 68–95–99.7 Rule; The Standard Normal Distribution • Estimate the relative locations of the median and mean on a density curve.
• Use the 68–95–99.7 rule to estimate areas (proportions of values) in a Normal distribution.
• Use Table A or technology to find (i) the proportion of z-values in a specified interval; or (ii) a z-score from a percentile in the standard Normal distribution. 33; 35; 39; 41; 43; 45; 47; 49; 51
3 2.2 Normal Distribution Calculations • Use Table A or technology to find (i) the proportion of values in a specified interval; or (ii) the value that corresponds to a given percentile in any Normal distribution. 53; 55; 57; 59
4 2.2 Assessing Normality • Determine if a distribution of data is approximately Normal from graphical and numerical evidence. 54; 63; 65; 66; 67; 69–74
5 Chapter 2 Review/FRAPPY! Chapter 2 Review Exercises
6 Chapter 2 Test

Chapter 3
Day Topics Learning Objectives Students will be able to … Suggested assignment
1 Chapter 3 Introduction
3.1 Explanatory and response variables; displaying relationships: scatterplots; describing scatterplots • 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 a relationship displayed in a scatterplot and recognize outliers in a scatterplot. 1; 5; 7; 11; 13
1 3.1 Measuring linear association: correlation; facts about correlation • Interpret the correlation.
• Understand the basic properties of correlation; including how the correlation is influenced by outliers.
• Use technology to calculate correlation.
• Explain why association does not imply causation. 14–18; 21
2 3.2 Least-squares regression; interpreting a regression line; prediction; residuals • 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.
• Calculate and interpret residuals. 27–32; 35; 37; 39; 41; 45
3 3.2 Calculating the equation of the least-squares regression line; determining whether a linear model is appropriate: residual plots • Explain the concept of least squares.
• Determine the equation of a least-squares regression line using technology.
• Construct and interpret residual plots to assess if a linear model is appropriate. 43; 47; 49; 51
4 3.2 How well the line fits the data: the role of s and r2 in regression • Interpret the standard deviation of the residuals and and use these values to assess how well the least-squares regression line models the relationship between two variables. 48; 50; 55; 58
5 3.2 Interpreting computer regression output; regression to the mean; correlation and regression wisdom • Determine the equation of a least-squares regression line using computer output.
• Describe how the slope; y intercept; standard deviation of the residuals; and are influenced by outliers.
• Find the slope and y intercept of the least-squares regression line from the means and standard deviations of x and y and their correlation. 59; 61; 63; 65; 69; 71–78
6 Chapter 3 Review/FRAPPY! Chapter Review Exercises
7 Chapter 3 Test

Chapter 4
Day Topics Learning Objectives Students will be able to… Suggested assignment
1 4.1 Introduction; The Idea of a Sample Survey; How to Sample Badly; How to Sample Well: Simple Random Sampling • Identify the population and sample in a statistical study.
• Identify voluntary response samples and convenience samples. Explain how these sampling methods can lead to bias.
• Describe how to obtain a random sample using slips of paper; technology; or a table of random digits. 1; 3; 5; 7; 9; 11
1 4.1 Other Random Sampling Methods • Distinguish a simple random sample from a stratified random sample or cluster sample. Give the advantages and disadvantages of each sampling method. 13; 17; 19; 21; 23; 25
2 4.1 Inference for Sampling; Sample Surveys: What Can Go Wrong? • Explain how undercoverage; nonresponse; question wording; and other aspects of a sample survey can lead to bias. 27; 29; 31; 33; 35
3 4.2 Observational Study versus Experiment; The Language of Experiments • Distinguish between an observational study and an experiment.
• Explain the concept of confounding and how it limits the ability to make cause-and-effect conclusions. 37–42; 45; 47; 49; 51; 53; 55
4 4.2 How to Experiment Badly; How to Experiment Well; Completely Randomized Designs • Identify the experimental units; explanatory and response variables; and treatments.
• Explain the purpose of comparison; random assignment; control; and replication in an experiment.
• Describe a completely randomized design for an experiment; including how to randomly assign treatments using slips of paper; technology; or a table of random digits. 57; 59; 61; 63; 65
5 4.2 Experiments: What Can Go Wrong? Inference for Experiments • Describe the placebo effect and the purpose of blinding in an experiment.
• Interpret the meaning of statistically significant in the context of an experiment. 67; 69; 71; 73

6 4.2 Blocking • Explain the purpose of blocking in an experiment.
• Describe a randomized block design or a matched pairs design for an experiment. 75; 77; 79; 81; 85
7 4.3 Scope of Inference; The Challenges of Establishing Causation • Describe the scope of inference that is appropriate in a statistical study. 83; 87–94; 97–104
7 4.3 Data Ethics (optional topic) • Evaluate whether a statistical study has been carried out in an ethical manner. Chapter 4 Review Exercises
8 Chapter 4 Review/FRAPPY! Chapter 4 AP® Practice Exam
9 Chapter 4 Test Cumulative AP Practice Test 1
Chapter 4 Project: Students work in teams of 2 to design and carry out an experiment to investigate response bias; write a summary report; and give a 10 minute oral synopsis to their classmates. See rubric on page 14.
Chapter 5
Day Topics Learning Objectives Students will be able to… Suggested assignment
1 5.1 The Idea of Probability; Myths about Randomness • Interpret probability as a long-run relative frequency. 1; 3; 7; 9; 11
1 5.1 Simulation • Use simulation to model chance behavior. 15; 17; 19; 23; 25
2 5.2 Probability Models; Basic Rules of Probability • Determine a probability model for a chance process.
• Use basic probability rules; including the complement rule and the addition rule for mutually exclusive events. 27; 31; 32; 39; 41; 43; 45; 47
2 5.2 Two-Way Tables; Probability; and the General Addition Rule; Venn Diagrams and Probability • Use a two-way table or Venn diagram to model a chance process and calculate probabilities involving two events.
• Use the general addition rule to calculate probabilities. 29; 33–36; 49; 51; 53; 55
3 5.3 What Is Conditional Probability?; The General Multiplication Rule and Tree Diagrams; • Calculate and interpret conditional probabilities.
• Use the general multiplication rule to calculate probabilities.
• Use tree diagrams to model a chance process and calculate probabilities involving two or more events. 57–60; 63; 65; 67; 71; 73; 77; 79
3 5.3 Conditional Probability and Independence: A Special Multiplication Rule • Determine whether two events are independent.
• When appropriate; use the multiplication rule for independent events to compute probabilities. 81; 83; 85; 89; 91; 93; 95; 97–99
4 Chapter 5 Review/FRAPPY! Chapter 5 Review Exercises
5 Chapter 5 Test
Chapter 6
Day Topics Learning Objectives Students will be able to… Suggested assignment
1 Chapter 6 Introduction; 6.1 Discrete Random Variables; Mean (Expected Value) of a Discrete Random Variable • Compute probabilities using the probability distribution of a discrete random variable.
• Calculate and interpret the mean (expected value) of a discrete random variable. 1; 3; 5; 7; 9; 11; 13
1 6.1 Standard Deviation (and Variance) of a Discrete Random Variable; Continuous Random Variables • Calculate and interpret the standard deviation of a discrete random variable.
• Compute probabilities using the probability distribution of a continuous random variable. 14; 15; 17; 18; 21; 23; 25
2 6.2 Linear Transformations • Describe the effects of transforming a random variable by adding or subtracting a constant and multiplying or dividing by a constant. 27–30; 35; 37; 39–41; 43; 45
2 6.2 Combining Random Variables; Combining Normal Random Variables • Find the mean and standard deviation of the sum or difference of independent random variables.
• Find probabilities involving the sum or difference of independent Normal random variables. 47; 49; 51; 53; 55; 57–59; 61
3 6.3 Binomial Settings and Binomial Random Variables; Binomial Probabilities • Determine whether the conditions for using a binomial random variable are met.
• Compute and interpret probabilities involving binomial distributions. 63; 65; 66; 69; 71; 73; 75; 77
4 6.3 Mean and Standard Deviation of a Binomial Distribution; Binomial Distributions in Statistical Sampling • Calculate the mean and standard deviation of a binomial random variable. Interpret these values in context. 79; 81; 83; 85; 87; 89
5 6.3 Geometric Random Variables • Find probabilities involving geometric random variables. 93; 95; 97; 99; 101–104
6 Chapter 6 Review/FRAPPY! Chapter 6 Review Exercises
7 Chapter 6 Test
EXAM REVIEW: 1 DAYS (Distribute review at the beginning of the chapter)
MIDTERM EXAM: Simulated AP format with Multiple Choice; Free Response
Chapter 7
Day Topics Learning Objectives Students will be able to… Suggested assignment
1 Introduction: German Tank Problem; 7.1 Parameters and Statistics • Distinguish between a parameter and a statistic. 1; 3; 5
1 7.1 Sampling Variability; Describing Sampling Distributions • Distinguish among the distribution of a population; the distribution of a sample; and the sampling distribution of a statistic.
• Use the sampling distribution of a statistic to evaluate a claim about a parameter.
• Determine whether or not a statistic is an unbiased estimator of a population parameter.
• Describe the relationship between sample size and the variability of a statistic. 7; 9; 11; 13; 15; 17; 19
2 7.2 The Sampling Distribution of ; Using the Normal Approximation for .
• Find the mean and standard deviation of the sampling distribution of a sample proportion . Check the 10% condition before calculating .
• Determine if the sampling distribution of is approximately Normal.
• If appropriate; use a Normal distribution to calculate probabilities involving .
21–24; 27; 29; 33; 35; 37; 39
3 7.3 The Sampling Distribution of : Mean and Standard Deviation; Sampling from a Normal Population • Find the mean and standard deviation of the sampling distribution of a sample mean . Check the 10% condition before calculating .
• If appropriate; use a Normal distribution to calculate probabilities involving .
43–46; 49; 51; 53; 55
4 7.3 The Central Limit Theorem • Explain how the shape of the sampling distribution of is affected by the shape of the population distribution and the sample size.
• If appropriate; use a Normal distribution to calculate probabilities involving .
57; 59; 61; 63; 65–68
5 Chapter 7 Review/FRAPPY! Chapter 7 Review Exercises
6 Chapter 7 Test Cumulative AP® Practice Exam 2
Chapter 8
Day Topics Learning objectives Students will be able to… Suggested assignment
1 Chapter 8 Introduction; 8.1 The Idea of a Confidence Interval; Interpreting Confidence Intervals and Confidence Levels • Interpret a confidence interval in context.
• Interpret a confidence level in context. 1; 3; 5; 7; 9
1 8.1 Constructing a Confidence Interval; Using Confidence Intervals Wisely • Determine the point estimate and margin of error from a confidence interval.
• Describe how the sample size and confidence level affect the length of a confidence interval.
• Explain how practical issues like nonresponse; undercoverage; and response bias can affect the interpretation of a confidence interval. 10; 11; 13; 15; 17; 19
2 8.2 Conditions for Estimating p; Constructing a Confidence Interval for p; Putting It All Together: The Four-Step Process • State and check the Random; 10%; and Large Counts conditions for constructing a confidence interval for a population proportion.
• Determine critical values for calculating a C% confidence interval for a population proportion using a table or technology.
• Construct and interpret a confidence interval for a population proportion. 20–24; 31; 33; 35; 37
2 8.2 Choosing the Sample Size • Determine the sample size required to obtain a C% confidence interval for a population proportion with a specified margin of error. 39; 41; 43; 45; 47
3 8.3 The Problem of unknown ; When Is Unknown: The t Distributions; Conditions for Estimating
• Explain how the t distributions are different from the standard Normal distribution and why it is necessary to use a t distribution when calculating a confidence interval for a population mean.
• Determine critical values for calculating a C% confidence interval for a population mean using a table or technology.
• State and check the Random; 10%; and Normal/Large Sample conditions for constructing a confidence interval for a population mean. 49–52; 55; 57; 59
4 8.3 Constructing a Confidence Interval for ; Choosing a Sample Size • Construct and interpret a confidence interval for a population mean.
• Determine the sample size required to obtain a C% confidence interval for a population mean with a specified margin of error. 61; 65; 69; 71; 73; 75–78
5 Chapter 8 Review/FRAPPY! Chapter 8 Review Exercises
6 Chapter 8 Test
Chapter 9
Day Topics Learning Objectives Students will be able to… Suggested assignment
1 9.1 Stating Hypotheses; The Reasoning of Significance Tests; Interpreting P-values; Statistical Significance • State the null and alternative hypotheses for a significance test about a population parameter.
• Interpret a P-value in context.
• Determine if the results of a study are statistically significant and draw an appropriate conclusion using a significance level. 1; 3; 5; 7; 9; 11; 15
1 9.1 Type I and Type II Errors • Interpret a Type I and a Type II error in context; and give a consequence of each. 13; 17; 19; 21; 23
2 9.2 Carrying Out a Significance Test; The One-Sample z Test for a Proportion • State and check the Random; 10%; and Large Counts conditions for performing a significance test about a population proportion.
• Perform a significance test about a population proportion. 25–28; 31; 35; 39; 41
3 9.2 Two-Sided Tests; Why Confidence Intervals Give More Information; Type II Error and the Power of a Test • Use a confidence interval to draw a conclusion for a two-sided test about a population parameter.
• Interpret the power of a test and describe what factors affect the power of a test.
• Describe the relationship among the probability of a Type I error (significance level); the probability of a Type II error; and the power of a test. 43; 45; 47; 51; 53; 55; 57

4 9.3 Carrying Out a Significance Test for ; The One Sample t Test; Two-Sided Tests and Confidence Intervals • State and check the Random; 10%; and Normal/Large Sample conditions for performing a significance test about a population mean.
• Perform a significance test about a population mean.
• Use a confidence interval to draw a conclusion for a two-sided test about a population parameter. 59–62; 65; 69; 73; 77; 79

5 9.3 Inference for Means: Paired Data; Using Tests Wisely • Perform a significance test about a mean difference using paired data. 83; 85; 87; 89–91; 93;
95–102
6 Chapter 9 Review/FRAPPY! Chapter 9 Review Exercises
7 Chapter 9 Test
Chapter 10
Day Topics Learning Objectives Students will be able to… Suggested assignment
1 “Is Yawning Contagious?” Activity; 10.1 The Sampling Distribution of a Difference between Two Proportions • Describe the shape; center; and spread of the sampling distribution of
1; 3
1 10.1 Confidence Intervals for
• Determine whether the conditions are met for doing inference about
• Construct and interpret a confidence interval to compare two proportions. 5; 7; 9; 11
2 10.1 Significance Tests for Inference for Experiments • Perform a significance test to compare two proportions. 13; 15; 17; 21; 23
3 10.2 “Does Polyester Decay?” Activity; The Sampling Distribution of a Difference between Two Means • Describe the shape; center; and spread of the sampling distribution of
• Determine whether the conditions are met for doing inference about
31; 33; 35; 51
4 10.2 The Two-Sample t Statistic; Confidence Intervals for
• Construct and interpret a confidence interval to compare two means. 25–28; 37; 39
5 10.2 Significance Tests for ; Using Two-Sample t Procedures Wisely • Perform a significance test to compare two means.
• Determine when it is appropriate to use two-sample t procedures versus paired t procedures. 41; 43; 45; 47; 53; 57–60
6 Chapter 10 Review/ FRAPPY! Chapter 10 Review Exercises
7 Chapter 10 Test Cumulative AP® Practice Exam 3
Chapter 11
Day Topics Learning objectives Students will be able to… Suggested assignment
1 Activity: The Candy Man Can; 11.1 Comparing Observed and Expected Counts: The Chi-Square Statistic; The Chi-Square Distributions and P-values • State appropriate hypotheses and compute expected counts for a chi-square test for goodness of fit.
• Calculate the chi-square statistic; degrees of freedom; and P-value for a chi-square test for goodness of fit. 1; 3; 5
2 11.1 Carrying Out a Test; Follow-Up Analysis • Perform a chi-square test for goodness of fit.
• Conduct a follow-up analysis when the results of a chi-square test are statistically significant. 7; 9; 11; 15; 17
3 11.2 Comparing Distributions of a Categorical Variable; Expected Counts and the Chi-Square Statistic; The Chi-Square Test for Homogeneity • Compare conditional distributions for data in a two-way table.
• State appropriate hypotheses and compute expected counts for a chi-square test based on data in a two-way table.
• Calculate the chi-square statistic; degrees of freedom; and P-value for a chi-square test based on data in a two-way table.
• Perform a chi-square test for homogeneity. 19–22; 27; 29; 31; 33; 35; 37; 39
4 11.2 Relationships between Two Categorical Variables; the Chi-Square Test for Independence; Using Chi-Square Tests Wisely • Perform a chi-square test for independence.
• Choose the appropriate chi-square test. 41; 43; 45; 47; 49; 51–55
5 Chapter 11 Review/Test Chapter 11 Review Exercises

Chapter 12
Day Topics Learning Objectives Students will be able to … Suggested assignment
1 Activity: The Helicopter Experiment; 12.1 Sampling Distribution of b; Conditions for Regression Inference • Check the conditions for performing inference about the slope of the population (true) regression line. 1; 3
1 12.1 Estimating the Parameters; Constructing a Confidence Interval for the Slope • Interpret the values of a; b; s; ; and in context; and determine these values from computer output.
• Construct and interpret a confidence interval for the slope of the population (true) regression line. 5; 7; 9; 11
2 12.1 Performing a Significance Test for the Slope • Perform a significance test about the slope of the population (true) regression line.
13; 15; 17
3 12.2 Transforming with Powers and Roots • Use transformations involving powers and roots to find a power model that describes the relationship between two variables; and use the model to make predictions. 19–24; 31; 33
4 12.2 Transforming with Logarithms; Putting it all Together: Which Transformation Should We Choose? • Use transformations involving logarithms to find a power model or an exponential model that describes the relationship between two variables; and use the model to make predictions.
• Determine which of several transformations does a better job of producing a linear relationship. 35; 37; 39; 41; 43; 45; 47–50
6 Chapter 12 Review/Test Chapter 12 Review Exercises
Cumulative AP® Practice Test 4

AP EXAM REVIEW
• Practice AP Free Response Questions
• Choosing the Correct Inference Procedure
• Flash cards
• Mock Grading Sessions
• Rubric development by student teams
• Practice Multiple Choice Questions

Introduction. In the introduction you should discuss what question you are trying to answer; why you chose this topic; what your hypotheses are; and how you will analyze your data.
Data Collection. In this section you will describe how you obtained your data. Be specific.
Graphs; Summary Statistics and the Raw Data (if numerical). Make sure the graphs are well labeled; easy to compare; and help answer the question of interest. You should include a brief discussion of the graphs and interpretations of the summary statistics.
Analysis. In this section; identify the inference procedure you used along with the test statistic and P-value and/or confidence interval. Also; discuss how you know that your inference procedure is valid.
Conclusion. In this section; you will state your conclusion. You should also discuss any possible errors or limitations to your conclusion; what you could do to improve the study next time; and any other critical reflections.
Live action pictures of your data collection in progress.

Presentation: You will be required to give a 5 minute oral presentation to the class.
The AP Statistics Exam is 3 hours long and seeks to determine how well a student
has mastered the concepts and techniques of the subject matter of the course. This
paper-and-pencil exam consists of (1) a 90-minute multiple-choice section testing
proficiency in a wide variety of topics; and (2) a 90-minute free-response section
requiring the student to answer open-ended questions and to complete an
investigative task involving more extended reasoning. In the determination of the
score for the exam; the two sections will be given equal weight.
Each student will be expected to bring a graphing calculator with statistical
capabilities to the exam. The expected computational and graphic features for these
calculators are described in an earlier section. Minicomputers; pocket organizers;
electronic writing pads (e.g.; Newton) and calculators with qwerty (i.e.; typewriter)
keyboards will not be allowed. Calculator memories will not be cleared. However;
calculator memories may be used only for storing programs; not for storing notes.
During the exam; students are not permitted to have access to any information in
their graphing calculators or elsewhere that is not directly related to upgrading the
statistical functionality of older graphing calculators to make them comparable to
statistical features found on newer models. Acceptable upgrades include improving
the calculator’s computational functionalities and/or graphical functionalities for
data that students key into the calculator while taking the exam. Unacceptable
enhancements include; but are not limited to; keying or scanning text or response
templates into the calculator. Students attempting to augment the capabilities of their
graphing calculators
in any way other than for the purpose of upgrading features as
described above will be considered to be cheating on the exam. A student may bring
up to two calculators to the exam.

Text: The Practice of Statistics (5th edition); by Starnes; Tabor; Yates; and Moore; W. H. Freeman & Co.; 2014.

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• 4 years of Math

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