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1 Introduction Learning Objectives By the end of this chapter, the student should be able to: - Recognize and differentiate between key terms. - Apply various types of sampling methods to data collection. - Create and interpret frequency tables. You are probably asking yourself the question, “When and where will I use statistics?” If you read any newspaper, watch television, or use the Internet, you will see statistical information. There are statistics about crime, sports, education, politics,

Chapters

• 1 Introduction
• 5 1.4 Levels of Measurement
• 6 1.5 Frequency & Frequency Tables
• 8 Introduction: Descriptive Statistics
• 9 2.1 Stem-and-Leaf Graphs, Line Graphs, Bar Graphs, and Pie Charts
• 12 2.4 Box Plots
• 13 2.5 Measures of the Center of the Data
• 14 2.6 Skewness and the Mean, Median, and Mode
• 16 2.8 When to use each measure of Central Tendency
• 17 Introduction: Probability Topics
• 18 3.1 The Terminology of Probability
• 19 3.2 Independent and Mutually Exclusive Events
• 20 3.3 Two Basic Rules of Probability
• 22 3.5 Tree and Venn Diagrams
• 24 4.1 Probability Distribution Function (PDF) for a Discrete Random Variable
• 26 4.3 Binomial Distribution
• 27 Geometric Distribution
• 31 6.2 Using the Normal Distribution
• 32 Introduction: The Central Limit Theorem
• 34 7.2 The Central Limit Theorem for Sums
• 35 7.3 Using the Central Limit Theorem
• 36 Introduction: Confidence Intervals
• 37 8.1 A Single Population Mean using the Normal Distribution
• 38 8.2 A Single Population Mean using the Student t Distribution
• 39 8.3 Confidence Interval for Population Proportion
• 40 Introduction: Hypothesis Testing with One Sample
• 41 9.1 Null and Alternative Hypotheses
• 42 9.2 Outcomes, Type I and Type II Errors
• 43 9.3 Distribution Needed for Hypothesis Testing
• 44 9.4 Rare Events, the Sample, Decision and Conclusion
• 46 Introduction: Linear Regression and Correlation
• 47 12.1 Linear Equations
• 49 12.3 The Regression Equation
• 50 12.4 Prediction

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