**Chapter 1: Data Collection**

1.1 Introduction to the Practice of Statistics

Objective 1: Define Statistics and Statistical Thinking

Objective 2: Explain the Process of Statistics

Objective 3: Distinguish between Qualitative and Quantitative Variables

Objective 4: Distinguish between Discrete and Continuous Variables

Objective 5: Determine the Level of Measurement of a Variable

1.2 Observational Studies versus Designed Experiments

Objective 1: Distinguish between an Observational Study and a Designed Experiment

Objective 2: Explain the Various Types of Observational Studies

1.3 Simple Random Sampling

Objective 1: Obtain a Simple Random Sample

1.4 Other Effective Sampling Methods

Objective 1: Obtain a Stratified Sample

Objective 2: Obtain a Systematic Sample

Objective 3: Obtain a Cluster Sample

1.5 Bias in Sampling

Objective 1: Explain the Sources of Bias in Sampling

1.6 The Design of Experiments

Objective 1: Describe the Characteristics of an Experiment

Objective 2: Explain the Steps in Designing an Experiment

Objective 3: Explain the Completely Randomized Design

Objective 4: Explain the Matched-Pairs Desig

Chapter 1 Review

Chapter 1 Test

Chapter 1 Projects

Making an Informed Decision: What College Should I Attend?

Case Study: Chrysalises for Cash

**Chapter 2: Organizing and Summarizing Data**

2.1 Organizing Qualitative Data

Objective 1: Organize Qualitative Data in Tables

Objective 2: Construct Bar Graphs

Objective 3: Construct Pie Charts

2.2 Organizing Quantitative Data: The Popular Displays

Objective 1: Organize Discrete Data in Tables

Objective 2: Construct Histograms of Discrete Data

Objective 3: Organize Continuous Data in Tables

Objective 4: Construct Histograms of Continuous Data

Objective 5: Draw Dot Plots

Objective 6: Identify the Shape of a Distribution

2.3 Additional Displays of Quantitative Data

Objective 1: Draw Stem-and-Leaf Plots

Objective 2: Construct Frequency Polygons

Objective 3: Create Cumulative Frequency and Relative Frequency Distributions

Objective 4: Construct Frequency and Relative Frequency Ogives

Objective 5: Draw Time-Series Graphs

2.4 Graphical Misrepresentations of Data

Objective 1: Describe What Can Make a Graph Misleading or Deceptive

Chapter 2 Review

Chapter 1 Test

Chapter 2 Projects

Making an Informed Decision: Tables or Graphs?

Case Study: The Day the Sky Roared

**Chapter 3: Numerically Summarizing Data**

3.1 Measures of Central Tendency

Objective 1: Determine the Arithmetic Mean of a Variable from Raw Data

Objective 2: Determine the Median of a Variable from Raw Data

Objective 3: Explain What It Means for a Statistic to be Resistant

Objective 4: Determine the Mode of a Variable from Raw Data

3.2 Measures of Dispersion

Objective 1: Determine the Range of a Variable from Raw Data

Objective 2: Determine the Standard Deviation of a Variable from Raw Data

Objective 3: Determine the Variance of a Variable from Raw Data

Objective 4: Use the Empirical Rule to Describe Data That Are Bell-Shaped

3.3 Measures of Central Tendency and Dispersion from Grouped Data

Objective 1: Approximate the Mean of a Variable from Grouped Data

Objective 2: Compute the Weighted Mean

Objective 3: Approximate the Standard Deviation from Grouped Data

3.4 Measures of Position

Objective 1: Determine and Interpret z-scores

Objective 2: Interpret Percentiles

Objective 3: Determine and Interpret Quartiles

Objective 4: Determine and Interpret the Interquartile Range

Objective 5: Check a Set of Data for Outliers

3.5 The Five-Number Summary and Boxplots

Objective 1: Determine the Five-Number Summary

Objective 2: Draw and Interpret Boxplots

Chapter 3 Review

Chapter 3 Test

Chapter 3 Projects

Making an Informed Decision: What Car Should I Buy?

Case Study: Who Was “A Mourner?”

**Chapter 4: Describing the Relation between Two Variables**

4.1 Scatter Diagrams and Correlation

Objective 1: Draw and Interpret Scatter Diagrams

Objective 2: Describe the Properties of the Linear Correlation Coefficient

Objective 3: Compute and Interpret the Linear Correlation Coefficient

Objective 4: Determine Whether a Linear Relation Exists between Two Variables

Objective 5: Explain the Difference between Correlation and Causation

4.2 Least-Squares Regression

Objective 1: Find the Least-Squares Regression Line and Use the Line to Make Predictions

Objective 2: Interpret the Slope and the y-Intercept of the Least-Squares Regression Line

Objective 3: Compute the Sum of Squared Residuals

4.3 Diagnostics on the Least-Squares Regression Line

Objective 1: Compute and Interpret the Coefficient of Determination

Objective 2: Perform Residual Analysis on a Regression Model

Objective 3: Identify Influential Observations

4.4 Contingency Tables and Association

Objective 1: Compute the Marginal Distribution of a Variable

Objective 2: Use the Conditional Distribution to Identify Association Among Categorical Data

Objective 3: Explain Simpson’s Paradox

Chapter 4 Review

Chapter 4 Test

Practice Test Problems

Chapter 4 Projects

Making an Informed Decision: Relations among Variables on a World Scale

"Case Study: Thomas Malthus, Population, and Subsistence"

**Chapter 5: Probability**

5.1 Probability Rules

Objective 1: Understand Random Processes and the Law of Large Numbers

Objective 2: Apply the Rules of Probabilities

Objective 3: Compute and Interpret Probabilities Using the Empirical Method

Objective 4: Compute and Interpret Probabilities Using the Classical Method

Objective 5: Recognize and Interpret Subjective Probabilities

5.2 The Addition Rule and Complements

Objective 1: Use the Addition Rule for Disjoint Events

Objective 2: Use the General Addition Rule

Objective 3: Compute the Probability of an Event Using the Complement Rule

5.3 Independence and the Multiplication Rule

Objective 1: Identify Independent Events

Objective 2: Use the Multiplication Rule for Independent Events

Objective 3: Compute At-Least Probabilities

Summary

5.4 Conditional Probability and the General Multiplication Rule

Objective 1: Compute Conditional Probabilities

Objective 2: Compute Probabilities Using the General Multiplication Rule

5.5 Counting Techniques

Objective 1: Solve Counting Problems Using the Multiplication Rule

Objective 2: Solve Counting Problems Using Permutations

Objective 3: Solve Counting Problems Using Combinations

Objective 4: Solve Counting Problems Involving Permutations with Nondistinct Items

Summary

Objective 5: Compute Probabilities Involving Permutations and Combinations

5.6 Simulation

Objective 1: Use Simulation to Obtain Probabilities

5.7 Putting It Together: Which Method Do I Use?

Objective 1: Determine the Appropriate Probability Rule to Use

Objective 2: Determine the Appropriate Counting Technique to Use

Chapter 5 Review

Chapter 5 Test

Chapter 5 Projects

Making an Informed Decision: What Are the Effects of Drinking and Driving?

Case Study: The Case of the Body in the Bag

**Chapter 6: Discrete Probability Distributions**

6.1 Discrete Random Variables

Objective 1: Distinguish between Discrete and Continuous Random Variables

Objective 2: Identify Discrete Probability Distributions

Objective 3: Graph Discrete Probability Distributions

Objective 4: Compute and Interpret the Mean of a Discrete Random Variable

Objective 5: Interpret the Mean of a Discrete Random Variable as an Expected Value

Objective 6: Compute the Standard Deviation of a Discrete Random Variable

6.2 The Binomial Probability Distribution

Objective 1: Determine Whether a Probability Experiment Is a Binomial Experiment

Objective 2: Compute Probabilities of Binomial Experiments

Objective 3: Compute the Mean and Standard Deviation of a Binomial Random Variable

Objective 4: Graph a Binomial Probability Distribution

6.3 The Poisson Probability Distribution

Objective 1: Determine Whether a Probability Experiment Follows a Poisson Process

Objective 2: Compute Probabilities of a Poisson Random Variable

Objective 3: Find the Mean and Standard Deviation of a Poisson Random Variable

Chapter 6 Review

Chapter 6 Test

Chapter 6 Projects

Making an Informed Decision: Should We Convict?

Case Study: The Voyage of the St. Andrew

**Chapter 7: The Normal Probability Distribution**

7.1 Properties of the Normal Distribution

Objective 1: Use the Uniform Probability Distribution

Objective 2: Graph a Normal Curve

Objective 3: State the Properties of the Normal Curve

Objective 4: Explain the Role of Area in the Normal Density Function

7.2 Applications of the Normal Distribution

Objective 1: Find and Interpret the Area under a Normal Curve

Objective 2: Find the Value of a Normal Random Variable

7.3 Assessing Normality

Objective 1: Use Normal Probability Plots to Assess Normality

7.4 The Normal Approximation to the Binomial Probability Distribution

Objective 1: Approximate Binomial Probabilities Using the Normal Distribution

Chapter 7 Review

Chapter 7 Test

Chapter 7 Projects

Making an Informed Decision: Which Stock Do I Pick?

Case Study: A Tale of Blood Chemistry

**Chapter 8: Sampling Distributions**

8.1 Distribution of the Sample Mean

Objective 1: Describe the Distribution of the Sample Mean: Normal Population

Objective 2: Describe the Distribution of the Sample Mean: Non-normal Population

Summary

8.2 Distribution of the Sample Proportion

Objective 1: Describe the Sampling Distribution of a Sample Proportion

Objective 2: Compute Probabilities of a Sample Proportion

Chapter 8 Review

Chapter 8 Test

Chapter 8 Projects

Making an Informed Decision: How Would You Break Down Your Day?

Case Study: Sampling Distribution of the Median

**Chapter 9: Estimating the Value of a Parameter**

9.1 Estimating a Population Proportion

Objective 1: Obtain a Point Estimate for the Population Proportion

Objective 2: Construct and Interpret a Confidence Interval for the Population Proportion

Objective 3: Determine the Sample Size Necessary for Estimating a Population Proportion within a Specified Margin of Error

9.2 Estimating a Population Mean

Objective 1: Obtain a Point Estimate for the Population Mean

Objective 2: State Properties of Student’s t-Distribution

Objective 3: Determine t-Values

Objective 4: Construct and Interpret a Confidence Interval for a Population Mean

Objective 5: Determine the Sample Size Necessary for Estimating a Population Mean within a Given Margin of Error

9.3 Putting It Together: Which Procedure Do I Use?

Objective 1 Determine the Appropriate Confidence Interval to Construct

9.4 Estimating with Bootstrapping

Objective 1: Estimate a Parameter Using the Bootstrap Method

Chapter 9 Review

Chapter 9 Test

Chapter 9 Projects

Making an Informed Decision: How Much Should I Spend for this House?

Case Study: Fire-Safe Cigarettes

**Chapter 10: Hypothesis Tests Regarding a Parameter**

10.1 The Language of Hypothesis Testing

Objective 1: Determine the Null and Alternative Hypotheses

Objective 2: Explain Type I and Type II Errors

Objective 3: State Conclusions to Hypothesis Tests

10.2 Hypothesis Tests for a Population Proportion

Objective 1: Explain the Logic Of Hypothesis Testing

Objective 2: Test Hypotheses about a Population Proportion

Objective 3: Test Hypotheses about a Population Proportion Using the Binomial Probability Distribution

10.2A Hypothesis Tests on a Population Proportion with Simulation

Objective 1: Explain the Logic of the Simulation Method

Objective 2: Test Hypotheses about a Population Proportion Using the Simulation Method

10.2B Hypothesis Tests on a Population Proportion Using the Normal Model

Objective 1: Explain the Logic of Hypothesis Testing Using the Normal Model

Objective 2: Test Hypotheses about a Population Using the Normal Model

Objective 3: Test Hypotheses about a Population Using the Binomial Probability Distribution

10.3 Hypothesis Tests for a Population Mean

Objective 1: Test Hypotheses about a Population Mean

Objective 2: Explain the Difference between Statistical Significance and Practical Significance

10.3A Hypothesis Tests on a Population Mean Using Simulation and the Bootstrap

Objective 1: Test Hypotheses about a Population Mean Using the Simulation Method

Objective 2: Test Hypotheses about a Population Mean Using the Bootstrap

10.4 Putting It Together: Which Procedure Do I Use?

Objective 1: Determine the Appropriate Hypothesis Test to Perform

Chapter 10 Review

Chapter 10 Test

Chapter 10 Projects

Making an Informed Decision: Which Mutual Fund Should I Choose?

Case Study: How Old Is Stonehenge?

**Chapter 11: Inference on Two Population Parameters**

11.1 Inference about Two Population Proportions: Independent Samples

Objective 1: Distinguish between Independent and Dependent Sampling

Objective 2: Test Hypotheses Regarding Two Population Proportions from Independent Samples

Objective 3: Construct and Interpret Confidence Intervals for the Difference between Two Population Proportions

Objective 4: Determine the Sample Size Necessary for Estimating the Difference between Two Population Proportions

11.1A Using Randomization Techniques to Compare Two Proportions

Objective 1: Use Randomization to Compare Two Population Proportions

11.2 Inference about Two Population Means: Dependent Samples

Objective 1: Test Hypotheses for a Population Mean from Matched-Pairs Data

Objective 2: Construct and Interpret Confidence Intervals about a Population Mean Difference of Matched-Pairs Data

11.2A Using Bootstrapping to Conduct Inference on Two Dependent Means

Objective 1: Test Hypotheses about Two Dependent Means Using the Bootstrap Method

11.3 Inference about Two Population Means: Independent Samples

Objective 1: Test Hypotheses Regarding Two Population Means from Independent Samples

Objective 2: Construct and Interpret Confidence Intervals about the Difference of Two Independent Means

11.3A Using Randomization Techniques to Compare Two Independent Means

Objective 1: Use Randomization to Compare Two Population Means

11.4 Putting It Together: Which Procedure Do I Use?

Objective 1: Determine the Appropriate Hypothesis Test to Perform

Chapter 11 Review

Chapter 11 Test

Chapter 11 Projects

Making an Informed Decision: Which Car Should I Buy?

Case Study: Control in the Design of an Experiment

**Chapter 12: Inference on Categorical Data**

12.1 Goodness-of-Fit Test

The Chi-Square Distribution

Objective 1: Perform a Goodness-of-Fit Test

12.2 Tests for Independence and the Homogeneity of Proportions

Objective 1: Perform a Test for Independence

Objective 2: Perform a Test for Homogeneity of Proportions

12.3 Inference about Two Population Proportions: Dependent Samples

Objective 1: Test Hypotheses Regarding Two Proportions from Dependent Samples

Chapter 12 Review

Chapter 12 Test

Chapter 12 Projects

Making an Informed Decision: What Are the Benefits of College?

"Case Study: Feeling Lucky? Well, Are You? "

**Chapter 13: Comparing Three or More Means**

13.1 Comparing Three or More Means: One-Way Analysis of Variance

Introduction to One-Way Analysis of Variance

Objective 1: Verify the Requirements to Perform a One-Way ANOVA

Objective 2: Test a Hypothesis Regarding Three or More Means Using One-Way ANOVA

13.2 Post Hoc Tests on One-Way Analysis of Variance

Objective 1: Perform Tukey's Test

Chapter 13 Review

Chapter 13 Test

Chapter 13 Projects

Making an Informed Decision: Where Should I Invest?

Case Study: Hat Size and Intelligence

**Chapter 14: Inference on the Least-Squares Regression Model and Multiple Regression**

14.1 Testing the Significance of the Least-Squares Regression Model

Review of Least-Squares Regression

Objective 1: State the Requirements of the Least-Squares Regression Model

Objective 2: Compute the Standard Error of the Estimate

Objective 3: Verify That the Residuals Are Normally Distributed

Objective 4: Conduct Inference on the Slope of the Least-Squares Regression Model

Objective 5: Construct a Confidence Interval about the Slope of the Least-Squares Regression Model

14.1A Using Randomization Techniques on the Slope of the Least-Squares Regression Line

Objective 1: Use Randomization to Test the Significance of the Slope of the Least-Squares Regression Model

14.2 Confidence and Prediction Intervals

Confidence and Prediction Intervals

Objective 1 Construct Confidence Intervals for a Mean Response

Objective 2 Construct Prediction Intervals for an Individual Response

14.3 Introduction to Multiple Regression **(NEW!)**

Objective 1 Obtain the Correlation Matrix

Objective 2 Use Technology to Find a Multiple Regression Equation

Objective 3 Interpret the Coefficients of a Multiple Regression Equation

Objective 4 Determine R2 and Adjusted R2

Objective 5 Perform an F-Test for Lack of Fit

Objective 6 Test Individual Regression Coefficients for Significance

Objective 7 Construct Confidence and Prediction Intervals

Multicollinearity Revisited

Chapter 14 Review

Chapter 14 Test

Chapter 14 Projects

Making an Informed Decision: What Should I Pay for this Home?

Case Study: Housing Boom

**Appendix A Tables and Formulas**

**Appendix B Lines**

Objective 1: Calculate and Interpret the Slope of a Line

"Objective 2: Graph Lines, Given a Point and the Slope"

Objective 3: Use the Point-Slope Form of a Line; Identify Horizontal Lines

"Objective 4: Find the Equation of a Line, Given Two Points"

Objective 5: Identify the Slope and y-Interecept of a Line from Its Equation

**Appendix C Inference on a Population Standard Deviation (NEW!)**

C.1 Estimating a Population Standard Deviation

Objective 1: Find Critical Values for the Chi-Square Distribution

Objective 2: Construct and Interpret Confidence Intervals for the Population Variance and Standard Deviation

C.2 Hypothesis Tests for a Population Standard Deviation

Objective 1: Test Hypotheses about a Population Standard Deviation