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Master Math: AP® Statistics

Book Description

Get ready to master the concepts of AP Statistics and ace your exam! MasterMath: AP® Statistics is a comprehensive reference guide written specifically for AP Statistics students, covering all the topics of AP Statistics in a simple, easy-to-follow style and format. Suitable for a wide variety of ability levels, this book explains and clarifies the various concepts of AP Statistics including exploring data, sampling and experimentation, anticipating patterns, and statistical inference. The example problems in each chapter are written with the AP Statistics Exam in mind to help you understand the concepts and learn how to effectively answer the exam questions. You'll also find useful appendices that will help you prepare for the exam, including all the tables and formulas that are given and needed, as well as a quick-reference summary of assumptions and conditions for inference. A helpful glossary will help you brush up on terminology. Master Math: AP® Statistics is an invaluable resource for anyone studying and preparing for the AP Statistics Exam.

Table of Contents

  1. Copyright
  2. Acknowledgments
  3. About the Author
  4. Introduction
  5. Preparing for the AP Statistics Exam
    1. Plan for Success
    2. How AP Grades Are Determined
  6. 1. Exploring and Graphing Univariate Data
    1. 1.1 Describing Distributions
      1. Shape, Center, and Spread
      2. Variance
      3. Standard Deviation
    2. 1.2 Displaying Data with Graphs
      1. Modified Boxplots
      2. Histograms
      3. Stemplots
      4. Dotplots
      5. Bar Graphs
      6. Pie Charts
  7. 2. Exploring and Graphing Bivariate Data
    1. 2.1 Scatterplots
      1. Correlation
      2. Facts about Correlation
      3. Least Squares Regression
      4. Facts about Regression
    2. 2.2 Modeling Data
  8. 3. Normal Distributions
    1. 3.1 Density Curves
    2. 3.2 Normal Distributions
      1. The Empirical Rule (the 68, 95, 99.7 Rule)
    3. 3.3 Normal Calculations
      1. Assessing Normality
  9. 4. Samples, Experiments, and Simulations
    1. 4.1 Sampling
    2. 4.2 Designing Experiments
    3. 4.3 Simulation
  10. 5. Probability
    1. 5.1 Probability and Probability Rules
    2. 5.2 Conditional Probability and Bayes’s Rule
    3. 5.3 Discrete Random Variables
    4. 5.4 Continuous Random Variables
    5. 5.5 Binomial Distributions
    6. 5.6 Geometric Distributions
  11. 6. Sampling Distributions
    1. 6.1 Sampling Distributions
    2. 6.2 Sample Means and the Central Limit Theorem
    3. 6.3 Sample Proportions and the Central Limit Theorem
  12. 7. Inference for Means
    1. 7.1 The t-Distributions
    2. 7.2 One-Sample t-Interval for the Mean
      1. Interpreting Confidence Intervals
    3. 7.3 One-Sample t-Test for the Mean
    4. 7.4 Two-Sample t-Interval for the Difference Between Two Means
    5. 7.5 Two-Sample t-Test for the Difference Between Two Means
    6. 7.6 Matched Pairs (One-Sample t)
    7. 7.7 Errors in Hypothesis Testing: Type I, Type II, and Power
  13. 8. Inference for Proportions
    1. 8.1 One-Sample z-Interval for Proportions
      1. Margin of Error
    2. 8.2 One-Sample z-Test for Proportions
    3. 8.3 Two-Sample z-Interval for Difference Between Two Proportions
    4. 8.4 Two-Sample z-Test for Difference Between Two Proportions
  14. 9. Inference for Related Variables: Chi-Square Distributions
    1. 9.1 The Chi-Square Statistic
    2. 9.2 Chi-Square Test for Goodness of Fit
    3. 9.3 Chi-Square Test for Homogeneity of Populations
    4. 9.4 Chi-Square Test for Independence/Association
  15. 10. Inference for Regression
    1. 10.1 The Regression Model
    2. 10.2 Confidence Intervals for the Slope β
    3. 10.3 Hypothesis Testing for the Slope β
  16. A. Tables
  17. B. Formulas
    1. Formulas Given on the AP Exam
      1. Descriptive Statistics
      2. Probability
      3. Inferential Statistics
    2. Formulas Not Given on the AP Exam
      1. Normal Distribution
      2. Probability
      3. Inferential Statistics
      4. Mean(s)
      5. Proportion(s)
      6. Regression
  18. C. Assumptions and Conditions for Inference
    1. One-sample t-interval or one-sample t-test
    2. Two-sample t-interval or two-sample t-test
    3. One-proportion z-interval or test
    4. Two-proportion z-interval or test
    5. Chi-square goodness of fit (one variable from one sample)
    6. Chi-square test for homogeneity (samples from many populations)
    7. Chi-square test for independence/association (one sample from one population classified on two variables)
    8. Regression (t)
  19. D. Glossary