## Table of Contents

(*NOTE: Each chapter begins with Where You’ve Been and Where Your Going sections and concludes with Uses and Abuses, Chapter Summary, Review Exercises, Chapter Quiz, Real Statistics-Real Decisions–Putting it all Together, and Technology sections*.)

**1. Introduction to Statistics.**

An Overview of Statistics. Data Classification. Case Study: Rating Television Shows in the United States. Experimental Design.

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**2. Descriptive Statistics.**

Frequency Distributions and Their Graphs. More Graphs and Displays. Measures of Central Tendency. Measures of Variation. Case Study: Sunglass Sales in the United States. Measures of Position.

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**3. Probability.**

Basic Concepts of Probability. Conditional Probability and the Multiplication Rule. The Addition Rule. Case Study: Probability and Parking Lot Strategies. Counting Principles.

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**4. Discrete Probability Distributions.**

Probability Distributions. Binomial Distributions. Case Study: Binomial Distribution of Airplane Accidents. More Discrete Probability Distributions.

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**5. Normal Probability Distributions.**

Introduction to Normal Distributions and the Standard Normal Distribution. Normal Distributions: Finding Probabilities. Normal Distributions: Finding Values.

Case Study: Birth Weights in America. The Central Limit Theorem. Normal Approximations to Binomial Distributions.

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**6. Confidence Intervals.**

Confidence Intervals for the Mean (Large Samples). Case Study: Shell Lengths of Loggerhead Sea Turtles. Confidence Intervals for the Mean (Small Samples). Confidence Intervals for Population Proportions. Confidence Intervals for Variance and Standard Deviation.

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**7. Hypothesis Testing with One Sample continue 2e p-value approach. **

Introduction to Hypothesis Testing. Hypothesis Testing for the Mean (Large Samples). Case Study: Human Body Temperature: What's Normal? Hypothesis Testing for the Mean (Small Samples). Hypothesis Testing for Proportions. Hypothesis Testing for the Variance and Standard Deviation.

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**8. Hypothesis Testing with Two Samples. **

Testing the Difference Between Means (Large Independent Samples). Case Study: Oatbran and Cholesterol Level. Testing the Difference Between Means (Small Independent Samples). Testing the Difference Between Means (Dependent Samples). Testing the Difference Between Proportions.

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**9. Correlation and Regression.**

Correlation. Linear Regression. Case Study: Correlation of Body Measurements. Measures of Regression and Prediction Intervals. Multiple Regression.

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**10. Chi-Square Tests and the F-Distribution.**

Goodness of Fit. Independence. Case Study: Traffic Safety Facts. Comparing Two Variances. Analysis of Variance.

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**11. Nonparametric Tests.**

The Sign Test. The Wilcoxon Tests. Case Study: Health and Nutrition. The Kruskal-Wallis Test. Rank Correlation. Runs Test.

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**Appendix A.**

Alternative Presentation of the Standard Normal Distribution. Standard Normal Distribution Table (0-to-z). Alternate Presentation of the Standard Normal Distribution.

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**Appendix B.**

Tables.