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

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