Primary Textbooks:
Yates, Daniel S, Daren S. Starnes, and David Moore. The Practice of Statistics, fifth edition. New York, NY: MacMillian, 2015.
Course Design
In our AP Statistics course we cover all of the items in the AP Statistics Course Description. In the AP Statistics class, students sit at tables that are pushed together to form clusters containing four to six students. Fostering important classroom discussion pertaining to topics such as methodology and inferences is supported by students working together in small groups.
All students have access to a TI83+ graphing calculator for use in class, at home, and on the AP Exam. Students will use their graphing calculators extensively throughout the course. Students also get the opportunity to get into the computer lab to complete projects and search for data.
Students will gain proficiency on accuracy and communication of statistical concepts throughout the course, to include effectively communicating how methods, results and interpretations of data for any given experiment are valid. They learn that writing complete responses using appropriate justifications is a critical aspect of gaining statistical proficiency.
Course Outline (Organized by chapters in primary textbook)
Year long course, Class length is 50 minutes
Chapter 1: Exploring Data (Total Time: 9 days)
Data Analysis: Making Sense of Data
Analyzing Categorical Data
Displaying Quantitative Data with Graphs
Displaying Quantitative Data with Numbers
Chapter 2: Modeling Distributions of Data (Total Time: 7 days)
Describing Location in a Distribution
Density Curves and Normal Distributions
Chapter 3: Describing Relationships (Total Time: 8 days)
Scatterplots and Correlation
Least-Square Regression
Using the TI-84
Understanding Computer Outputs
Chapter 4: Designing Studies (Total Time: 11 days)
Sampling and Surveys
Experiments
Using Studies Wisely
Chapter 5: Probability: What are the Chances? (Total Time: 8 days)
Randomness, Probability, and Simulation
Probability Rules
Conditional Probability and Independence
Estimating Probability Using Simulation Applets
Chapter 6: Random Variables (Total Time: 9 days)
Discrete and Continuous Random Variables
Transforming and Combining Random Variables
Binomial and Geometric Random Variables
Midterm Chapters 1-6 (Total Time: 4 days)
Review and Midterm
Chapter 7: Sampling Distributions (Total Time: 7 days)
What is a Sampling Distribution?
Sample Proportions
Sample Means
Chapter 8: Estimating with Confidence (Total Time: 8 days)
Confidence Intervals: The Basics
Estimating a Population Proportion
Estimating a Population Mean
Using the TI-84
Chapter 9: Testing a Claim (Total Time: 8 days)
Significance Test: The Basics
Tests about a Population Proportion
Tests about a Population Mean
Using the TI-84
Chapter 10: Comparing Two Populations or Groups (Total Time: 8 days)
Comparing Two Proportions
Comparing Two Means
Using the TI-84
Chapter 11: Inference for Distributions of Categorical Data (Total Time: 6 days)
Chi-Square Tests for Goodness of Fit
Inference for Two-Way Tables
Using the TI-84
Chapter 12: More About Regression (Total Time: 4 days)
Inference for Linear Regression
Transforming to Achieve Linearity
Final Exam (Total Time: 4 days)
Review and Final
AP Statistics Olympics Project
Students will design and conduct an experiment using all statistical techniques learned during the AP Statistics course. The project will be done in pairs. Students will turn in one project per pair, with a written report. Each experiment should have quantitative data so that a winner can be selected from each event. Student’s z-values are used from each event to calculate an overall winner of the Olympics. Other classes are invited to participate in the Olympics, so that each event has a significant sample size.
Proposal: The proposal should
Describe the event and how it is played
Describe how a winner is chosen
Describe an appropriate sample size
Poster: The poster should summarize the event yet be simple enough to be
understood by any participant.
Written Report: Students will submit a written report that includes the following:
Introduction: Why was the event chosen?
Methods: How was the event conducted? Was there any bias?
Results: Present the data in such a way that conclusions can easily be made.
Conclusions: Analyze the data using descriptive and inferential statistics, drawing conclusions from their analysis.