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Chapter 1: Exploring Data
Section 1.1: Displaying Distributions with Graphs
70111: Describing Distributions Visually
70112: More Visual Displays of Data
Section 1.2: Describing Distributions with Numbers
70121: Measures of Center and Spread
70122: Standard Deviation

Chapter 2: The Normal Distributions
Section 2.1: Density Curves and the Normal Distributions

70211: Density Curves
70212: Normal Distributions
Section 2.2: Standard Normal Calculations
70221: The Standard Normal Distribution
70222: Assessing Normality

70290: Unit 1 Review

Chapter 3: Relationships in Two-Variable Data
Section 3.1: Scatterplots

70311: Bivariate (two-variables) Scatterplots
70312: Categorical Variables in Scatterplots
Section 3.2: Correlation
70321: The Correlation Constant
Section 3.3: Least Squares Regression
70331: Linear Regression
70332: The Coefficient of Determination: r2
70333: Residuals and Residual Plots

Chapter 4: Nonlinear Two-Variable Data
Section 4.1: Modeling Nonlinear Data

70411: Exponential Regression
70412: Exponential Regression Practice
70413: Polynomial Regression
70414: Polynomial Regression Practice
70415: Regression Overview
Section 4.2: Interpreting Correlation and Regression
70421: Interpreting Correlation and Regression
Section 4.3: Relations in Categorical Data
70431: Associations in Categorical Data
70432: Simpson’s Paradox

70490: Unit 2 Review

Chapter 5: Producing Data
Section 5.1: Designing Samples

70511: Simple Random Samples
70512: Other Sampling Designs
70513: Sampling Activity
Section: 5.2: Designing Experiments
70521: Designing Experiments
70522: Three Principles of Experimental Design
70523: Block Design and Matched Pairs Design
Section: 5.3: Simulating Experiments
70531: Simulating Studies
70532: Simulating Experiments on the TI

Chapter 6: Probability
Section 6.0: Counting Theory

70601: Counting Theory (Permutation and Combination)
Section 6.1: Random Outcomes
70611: Randomness and Probability
Section 6.2: Probability Models
70621: Probability Basics
70622: Independent Events
70623: The Birthday Problem
70624: Permutation and Combination
Section 6.3: Conditional Probability
70631: Conditional Probability
70632: False Positives and Sensitive Surveys

70690: Unit 3 Review

Chapter 7: Random Variables
Section 7.1: Discrete and Continuous Random Variables

70711: Discrete Random Variables
70712: Continuous Random Variables
70713: Random Variables Work Day
Section 7.2: Means and Variances of Random Variables
70721: The Mean of a Discrete Random Variable
70722: The Variance of Random Variables
70723: Combining Two Random Variables: Means and Variances
70724: Random Variables Practice

Chapter 8: Binomial and Geometric Distributions
Section 8.1: The Binomial Distribution

70811: Binomial Probability
70812: Binomial PDF and CDF
70813: Simulations: Mean and Standard Deviation of Binomials
70814: Binomial Distribution Practice
Section 8.2: The Geometric Distribution
70821: The Geometric Distribution
70822: The Expected Value of Geometric Distributions

70890: Unit 4 Review

Chapter 9: Sampling Distributions
Section 9.1: Sampling Distributions

70911: Sampling Distributions
70912: Describing Sampling Distributions
Section 9.2: Sample Proportions
70921: Sample Proportions
Section 9.3: Sample Means
70931: Sample Means
70932: The Central Limit Theorem
70933: Chapter 9 Review- Work Day 9

Chapter 10: Introduction to Inference
Section 10.1: Confidence Intervals

71011: Statistical Confidence
71012: General Confidence Intervals
71013: Choosing Sample Size
71014: Section 10.1 Review- Workday 10.1
Section 10.2: Hypotheses & Significance Test
71021: Significance Tests
71022: Statistical Significance and Alpha Level
71023: The z Test Statistic & Two-sided Tests
71024: Section 10.2 Review- Workday 10.2
Section 10.3: Using Significance Tests
71031: Choosing Significance Level
Section 10.4: Making Decisions from Inference
71041: Type I and Type II Errors
71042: The POWER of a Hypothesis Test
71043: Section 10.4 Review- Workday 10.4

71090: Unit 5 Review

Chapter 11: Inference for Population Means
Section 11.1: One-Sample Means
71111: Applied Inference
71112: t Confidence Intervals & Tests
71113: Matched Pairs t Procedures
71114: The assumptions of a t-test and the power of a t-test
71115: Review- Workday 11.1
Section 11.2: Two-Sample Means
71121: Comparing Two Populations
71122: Two-sample tests on the TI

Chapter 12: Inference for Population Proportions
Section 12.1: One-Sample Proportions

71211: Inference for Proportions
71212: Minimum Sample Size & Proportions on TI
Section 12.2: Two-Sample Proportions
71221: Two-Sample Proportions
71222: Chapter 12 Review- Work Day 12

Chapter 13: Inference for Tables
Section 13.1: Test for Goodness of Fit

71311: The Great M&Ms Mystery
71312: Testing Distributions
71313: Simulating a Distribution
Section 13.2: Inference for Two-Way Tables
71321: Comparing Proportions for Multiple Populations
71322: Testing Associations in Categorical Variables
71323: Dice Day 

Chapter 14: Inference for Regression
Section 14.1: Inference about the Model

71411: Inference for Regression
71412: Confidence Intervals & Hypothesis Tests for Regression
Section 14.3: Checking Assumptions
71431: Regression Assumptions

Activities and Review
71490: Unit 6 Review
71511: The F Distributions
71610: The Time Value of Money
71620: The Principles of Investing
71630: Practical Investing Strategies

AP Statistics: Table of Contents

This course is designed as an instructional resource for Math and Statistics students, and to prepare advanced learners for the College Board AP Exam. Each lesson links to a downloadable PowerPoint (.ppt) file, and is associated with a section from the below referenced textbook (Yates). Please feel invited to freely download, edit, repurpose whatever you need; use or modify however is helpful. A full-course treatment with interactive practice, randomly generated exercises, and Inductive Pedagogy are on the development roadmap for 2020-2021 school year.

Reference Text:  The Practice of Statistics, First Edition.  Yates, Moore, McCabe |


This discipline is a technical and in-depth extension of probability and statistics for success on the Advanced Placement exam.

> California Department of Education Math Standards
> Advanced Placement Probability and Statistics

The linked syllabus is an 8-page MS Word (.doc) file. All material is free to download, edit, repurpose. To support development, the Course Reviews (A, B) each appear in the store for $5. Email if you need them without charge.

Course Review (A)

This is a PowerPoint presentation I use at the end of AP Statistics for whole-course review and as practice tool for the AP Exam.

The presentation contains 52 slides with 6 practice items from the 1999 AP exam (including solutions and scoring guides), and a review of high-level concepts including: Distributions, Regression, The mechanics of finding linear, polynomial, and exponential models, Experiments and Studies, Probability, Random Variables, Inference, and Assumptions.

Course Review (B)

This is a PowerPoint presentation designed for whole-course review and as practice tool for the AP Statistics Exam.

The presentation contains 56 slides with 6 practice items drawn from the 2000 AP exam (including solutions and scoring guides), and a review of high-level concepts including: Distributions, Regression, The mechanics of finding linear, polynomial, and exponential models, Experiments and Studies, Probability, Random Variables, Inference, and Assumptions.

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