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• Cover
• Introduction
• About This Book
• Foolish Assumptions
• Icons Used in This Book
• Beyond the Book
• Where to Go from Here
• Part 1: Getting Off to a Statistically Significant Start
• Chapter 1: Summarizing Categorical Data: Counts and Percents
• Counting On the Frequency
• Relating with Percentages
• Interpreting Counts and Percents with Caution
• Answers to Problems in Summarizing Categorical Data
• Chapter 2: Summarizing Quantitative Data: Means, Medians, and More
• Finding and Interpreting Measures of Center
• Finding and Interpreting Measures of Spread
• Using Percentiles and the Interquartile Range
• Answers to Problems in Summarizing Quantitative Data
• Chapter 3: Organizing Categorical Data: Charts and Graphs
• Making, Interpreting, and Evaluating Pie Charts
• Making, Interpreting, and Evaluating Bar Graphs
• Answers to Problems in Organizing Categorical Data
• Chapter 4: Organizing Quantitative Data: Charts and Graphs
• Creating a Histogram
• Making Sense of Histograms
• Straightening Out Skewed Data
• Spotting a Misleading Histogram
• Making Box Plots
• Interpreting Box Plots
• Looking at Line Graphs
• Understanding the Empirical Rule
• Answers to Problems in Organizing Quantitative Data
• Part 2: Probability, Distributions, and the Central Limit Theorem (Are You Having Fun Yet?)
• Chapter 5: Understanding Probability Basics
• Grasping the Rules of Probability
• Avoiding Probability Misconceptions
• Making Predictions Using Probability
• Answers to Problems in Probability
• Chapter 6: Measures of Relative Standing and the Normal Distribution
• Mastering the Normal Distribution
• Finding and Interpreting Standard (Z) Scores
• Knowing Where You Stand with Percentiles
• Finding Probabilities for a Normal Distribution
• Finding the Percentile (Backwards Normal)
• Answers to Problems in Normal Distribution
• Chapter 7: The Binomial Distribution
• Characterizing the Binomial Distribution
• Finding Probabilities Using the Binomial Formula for small n
• Finding Probabilities Using the Binomial Table for Medium-Sized n
• Calculating the Mean and Variance of the Binomial
• Estimating Probabilities in Large Cases — the Normal Approximation
• Answers to Problems in the Binomial Distribution
• Chapter 8: The t-Distribution
• Getting to Know the t-Distribution
• Working with the t-Table and Degrees of Freedom
• Answers to Problems in the t-Distribution
• Chapter 9: Demystifying Sampling Distributions and the Central Limit Theorem
• Exactly What Is a Sampling Distribution?
• Clearing Up the Central Limit Theorem (Once and for All)
• Finding Probabilities with the Central Limit Theorem
• When Your Sample’s Too Small: Employing the t-Distribution
• Answers to Problems in Sampling Distributions and the Central Limit Theorem
• Part 3: Guesstimating and Hypothesizing with Confidence
• Chapter 10: Making Sense of Margin of Error
• Reviewing Margin of Error
• Calculating the Margin of Error for Means and Proportions
• Increasing and Decreasing Margin of Error
• Interpreting Margin of Error Correctly
• Answers to Problems in Making Sense of Margin of Error
• Chapter 11: Calculating Confidence Intervals
• Walking through a Confidence Interval
• Deriving a Confidence Interval for a Population Mean
• Figuring a Confidence Interval for a Population Proportion
• Calculating a Confidence Interval for the Difference of Two Means
• Computing a Confidence Interval for the Difference of Two Proportions
• Answers to Problems in Calculating Confidence Intervals
• Chapter 12: Deciphering Your Confidence Interval
• Interpreting Confidence Intervals the Right Way
• Evaluating Confidence Interval Results: What the Formulas Don’t Tell You
• Answers to Problems in Confidence Intervals
• Chapter 13: Testing Hypotheses
• Walking Through a Hypothesis Test
• Testing a Hypothesis about a Population Mean
• Testing a Hypothesis about a Population Proportion
• Testing for a Difference between Two Population Means
• Testing for a Mean Difference (Paired t-Test)
• Testing a Hypothesis about Two Population Proportions
• Answers to Problems in Testing Hypotheses
• Chapter 14: Taking the Guesswork Out of p-Values and Type I and II Errors
• Understanding What p-Values Measure
• Test (Statistic) Time: Figuring Out p-Values
• The Value Breakdown: Interpreting p-Values Properly
• Deciphering Type I Errors
• Deciphering and Distinguishing Type II Errors
• Answers to Problems in p-Values and Type I and II Errors
• Part 4: Statistical Studies and the Hunt for a Meaningful Relationship
• Chapter 15: Examining Polls and Surveys
• Planning and Designing a Survey
• Selecting a Random Sample
• Carrying Out a Survey Properly
• Interpreting and Evaluating Survey Results
• Answers to Problems in Polls and Surveys
• Chapter 16: Evaluating Experiments
• Distinguishing Experiments from Observational Studies
• Designing a Good Experiment
• Looking for Cause and Effect: Interpreting Experiment Results
• Answers to Problems in Evaluating Experiments
• Chapter 17: Looking for Links in Categorical Data: Two-Way Tables
• Understanding Two-Way Tables Inside and Out
• Working with Intersection, Unions, and the Addition Rule
• Figuring Marginal Probabilities
• Nailing Down Conditional Probabilities and the Multiplication Rule
• Inspecting the Independence of Categorical Variables
• Answers to Problems in Two-Way Tables
• Chapter 18: Searching for Links in Quantitative Data: Correlation and Regression
• Relating X and Y with a Scatterplot
• Toeing the Line of Correlation
• Picking Out the Best Fitting Regression Line
• Interpreting the Regression Line and Making Predictions
• Checking the Fit of the Regression Line
• Answers to Problems in Correlation and Regression
• Part 5: The Part of Tens
• Chapter 19: Math Review: Ten Steps to a Better Grade
• Know Your Math Symbols
• Uproot Roots and Powers
• Treat Fractions with Extra Care
• Obey the Order of Operations
• Avoid Rounding Errors
• Get Comfortable with Formulas
• Stay Calm When Formulas Get Tough
• Feel Fine about Functions
• Know When Your Answer Is Wrong
• Show Your Work
• Chapter 20: Top Ten Statistical Formulas
• Mean (or Average)
• Median
• Sample Standard Deviation
• Correlation
• Margin of Error for the Sample Mean
• Sample Size Needed for Estimating μ
• Test Statistic for the Mean
• Margin of Error for the Sample Proportion
• Sample Size Needed for Estimating p
• Test Statistic for the Proportion
• Chapter 21: Ten Ways to Spot Common Statistical Mistakes
• Scrutinizing Graphs
• Searching for and Specifying Bias
• Marking the Margin of Error
• Scanning for Sample Size
• Studying Sample Selection (Gotta Be Random)
• Checking for Confounding Variables
• Considering Correlation
• Doing the Math
• Detecting Selective Reporting
• Avoiding the Anecdote
• Appendix: Tables for Reference
• Z-Table
• t-Table
• Binomial Table
• Index
• About the Author
• Advertisement Page
• Connect with Dummies
• End User License Agreement