Seeing Through Statistics 5th edition

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• Chapter 1: The Benefits and Risks of Using Statistics
  • 1: Concept Explorations
  • 1.1: Why Bother Reading This Book?
  • 1.2: What Is Statistics All About?
  • 1.3: Detecting Patterns and Relationships
  • 1.4: Don't Be Deceived by Improper Use of Statistics
  • 1.5: Summary and Conclusions
  • 1: Exercises
  • 1: Test Bank
  
  
• Chapter 2: Reading the News
  • 2: Concept Explorations
  • 2.1: The Educated Consumer of Data
  • 2.2: Origins of News Stories
  • 2.3: How to be a Statistics Sleuth: Seven Critical Components
  • 2.4: Four Hypothetical Examples of Bad Reports
  • 2.5: Planning Your Own Study: Defining the Components in Advance
  • 2: Exercises
  • 2: Test Bank
  
  
• Chapter 3: Measurements, Mistakes, and Misunderstandings
  • 3: Concept Explorations
  • 3.1: Simple Measures Don't Exist
  • 3.2: It's All in the Wording
  • 3.3: Open or Closed Questions: Should Choices Be Given?
  • 3.4: Defining What Is Being Measured
  • 3.5: Defining a Common Language
  • 3: Exercises
  • 3: Test Bank
  
  
• Chapter 4: How to Get a Good Sample
  • 4: Concept Explorations
  • 4.1: Common Research Strategies
  • 4.2: Defining a Common Language
  • 4.3: The Beauty of Sampling
  • 4.4: Simple Random Sampling
  • 4.5: Other Sampling Methods
  • 4.6: Difficulties and Disasters in Sampling
  • 4: Exercises
  • 4: Labs
  • 4: Test Bank
  
  
• Chapter 5: Experiments and Observational Studies
  • 5: Concept Explorations
  • 5.1: Defining a Common Language
  • 5.2: Designing a Good Experiment
  • 5.3: Difficulties and Disasters in Experiments
  • 5.4: Designing a Good Observational Study
  • 5.5: Difficulties and Disasters in Observational Studies
  • 5.6: Random Sample Versus Random Assignment
  • 5: Exercises
  • 5: Test Bank
  
  
• Chapter 6: Getting the Big Picture
  • 6: Concept Explorations
  • 6.1: Final Questions
  • 6: Exercises
  • 6: Test Bank
  
  
• Chapter 7: Summarizing and Displaying Measurement Data
  • 7: Concept Explorations
  • 7.1: Turning Data into Information
  • 7.2: Picturing Data: Stemplots and Histograms
  • 7.3: Five Useful Numbers: A Summary
  • 7.4: Boxplots
  • 7.5: Traditional Measures: Mean, Variance, and Standard Deviation
  • 7.6: Caution: Being Average Isn't Normal
  • 7: Exercises
  • 7: Test Bank
  
  
• Chapter 8: Bell-Shaped Curves and Other Shapes
  • 8: Concept Explorations
  • 8.1: Populations, Frequency Curves, and Proportions
  • 8.2: The Pervasiveness of Normal Curves
  • 8.3: Percentiles and Standardized Scores
  • 8.4: z-Scores and Familiar Intervals
  • 8: Exercises
  • 8: Labs
  • 8: Test Bank
  
  
• Chapter 9: Plots, Graphs, and Pictures
  • 9: Concept Explorations
  • 9.1: Well-Designed Statistical Pictures
  • 9.2: Pictures of Categorical Data
  • 9.3: Pictures of Measurement Variables
  • 9.4: Pictures of Trends Across Time
  • 9.5: Difficulties and Disasters in Plots, Graphs, and Pictures
  • 9.6: A Checklist for Statistical Pictures
  • 9: Exercises
  • 9: Labs
  • 9: Test Bank
  
  
• Chapter 10: Relationships Between Measurement Variables
  • 10: Concept Explorations
  • 10.1: Statistical Relationships
  • 10.2: Strength Versus Statistical Significance
  • 10.3: Measuring Strength Through Correlation
  • 10.4: Specifying Linear Relationships with Regression
  • 10: Exercises
  • 10: Labs
  • 10: Test Bank
  
  
• Chapter 11: Relationships Can Be Deceiving
  • 11: Concept Explorations
  • 11.1: Illegitimate Correlations
  • 11.2: Legitimate Correlation Does Not Imply Causation
  • 11.3: Some Reasons for Relationships Between Variables
  • 11.4: Confirming Causation
  • 11: Exercises
  • 11: Test Bank
  
  
• Chapter 12: Relationships Between Categorical Variables
  • 12: Concept Explorations
  • 12.1: Displaying Relationships Between Categorical Variables: Contingency Tables
  • 12.2: Relative Risk, Increased Risk, and Odds
  • 12.3: Misleading Statistics about Risk
  • 12.4: Simpson's Paradox: The Missing Third Variable
  • 12: Exercises
  • 12: Labs
  • 12: Test Bank
  
  
• Chapter 13: Statistical Significance for 2 × 2 Tables
  • 13: Concept Explorations
  • 13.1: Measuring the Strength of the Relationship
  • 13.2: Steps for Assessing Statistical Significance
  • 13.3: The Chi-Square Test
  • 13.4: Practical Versus Statistical Significance
  • 13: Exercises
  • 13: Labs
  • 13: Test Bank
  
  
• Chapter 14: Understanding Probability and Long-Term Expectations
  • 14: Concept Explorations
  • 14.1: Probability
  • 14.2: The Relative-Frequency Interpretation
  • 14.3: The Personal-Probability Interpretation
  • 14.4: Applying Some Simple Probability Rules
  • 14.5: When Will It Happen?
  • 14.6: Long-Term Gains, Losses, and Expectations
  • 14: Exercises
  • 14: Test Bank
  
  
• Chapter 15: Understanding Uncertainty through Simulation
  • 15: Concept Explorations
  • 15.1: Mimicking Reality through Simulation
  • 15.2: Simulating Probabilities
  • 15.3: Simulating the Chi-Square Test
  • 15.4: Randomization Tests
  • 15: Exercises
  • 15: Test Bank
  
  
• Chapter 16: Psychological Influences on Personal Probability
  • 16: Concept Explorations
  • 16.1: Revisiting Personal Probability
  • 16.2: Equivalent Probabilities but Different Decisions
  • 16.3: How Personal Probabilities Can Be Distorted
  • 16.4: Optimism, Reluctance to Change, and Overconfidence
  • 16.5: Calibrating Personal Probabilities of Experts
  • 16.6: Tips for Improving Your Personal Probabilities and Judgments
  • 16: Exercises
  • 16: Test Bank
  
  
• Chapter 17: When Intuition Differs from Relative Frequency
  • 17: Concept Explorations
  • 17.1: Revisiting Relative Frequency
  • 17.2: Coincidences
  • 17.3: The Gambler's Fallacy
  • 17.4: Confusion of the Inverse
  • 17.5: Using Expected Values to Make Wise Decisions
  • 17: Exercises
  • 17: Test Bank
  
  
• Chapter 18: Understanding the Economic News
  • 18: Concept Explorations
  • 18.1: Statistics and the Economy
  • 18.2: Cost of Living: The Consumer Price Index
  • 18.3: Uses of the Consumer Price Index
  • 18.4: Criticisms of the Consumer Price Index
  • 18.5: Seasonal Adjustments: Reporting the Consumer Price Index
  • 18.6: Economic Indicators
  • 18: Exercises
  • 18: Test Bank
  
  
• Chapter 19: The Diversity of Samples from the Same Population
  • 19: Concept Explorations
  • 19.1: Setting the Stage
  • 19.2: What to Expect of Sample Proportions
  • 19.3: What to Expect of Sample Means
  • 19.4: What to Expect in Other Situations
  • 19.5: Simulated Proportions and Means
  • 19: Exercises
  • 19: Labs
  • 19: Test Bank
  
  
• Chapter 20: Estimating Proportions with Confidence
  • 20: Concept Explorations
  • 20.1: Confidence Intervals
  • 20.2: Three Examples of Confidence Intervals from the Media
  • 20.3: Constructing a Confidence Interval for a Proportion
  • 20: Exercises
  • 20: Labs
  • 20: Test Bank
  
  
• Chapter 21: The Role of Confidence Intervals in Research
  • 21: Concept Explorations
  • 21.1: Confidence Intervals for Populations Means
  • 21.2: Confidence Intervals for the Difference Between Two Means
  • 21.3: Revisiting Case Studies and Examples: How Journals Present Confidence Intervals
  • 21.4: Understanding Any Confidence Interval
  • 21: Exercises
  • 21: Labs
  • 21: Test Bank
  
  
• Chapter 22: Rejecting Chance—Testing Hypotheses in Research
  • 22: Concept Explorations
  • 22.1: Using Data to Make Decisions
  • 22.2: The Basic Steps for Testing Hypotheses
  • 22.3: Testing Hypotheses for Proportions
  • 22.4: What Can Go Wrong: The Two Types of Errors
  • 22: Exercises
  • 22: Test Bank
  
  
• Chapter 23: Hypothesis Testing—Examples and Case Studies
  • 23: Concept Explorations
  • 23.1: How Hypothesis Tests Are Reported in the News
  • 23.2: Testing Hypotheses about Proportions and Means
  • 23.3: How Journals Present Hypothesis Tests
  • 23: Exercises
  • 23: Labs
  • 23: Test Bank
  
  
• Chapter 24: Significance, Importance, and Undetected Differences
  • 24: Concept Explorations
  • 24.1: Real Importance Versus Statistical Significance
  • 24.2: The Role of Sample Size in Statistical Significance
  • 24.3: No Difference Versus No Statistically Significant Difference
  • 24.4: Multiple Tests, Multiple Comparisons, and False Positives
  • 24.5: Addressing Criticisms of Hypothesis Testing
  • 24.6: A Summary of Warnings and Key Concepts
  • 24: Exercises
  • 24: Test Bank
  
  
• Chapter 25: Meta-Analysis: Resolving Inconsistencies across Studies
  • 25: Concept Explorations
  • 25.1: The Need for Meta-Analysis
  • 25.2: Two Important Decisions for the Analyst
  • 25.3: Some Benefits of Meta-Analysis
  • 25.4: Criticisms of Meta-Analysis
  • 25: Exercises
  • 25: Test Bank
  
  
• Chapter 26: Ethics in Statistical Studies
  • 26: Concept Explorations
  • 26.1: The Need for Ethics in Research Studies
  • 26.2: Ethical Treatment of Human and Animal Participants
  • 26.3: Assurance of Data Quality
  • 26.4: Appropriate Statistical Analyses
  • 26.5: Fair Reporting of Results
  • 26: Exercises
  • 26: Test Bank
  
  
• Chapter 27: Putting What You Have Learned to the Test
  • 27: Test Bank
  
  
• Chapter PJT: Project
  • PJT.1: Project