Bruce, Peter C.
Introductory Statistics and Analytics : A Resampling Perspective. - 1 online resource (309 pages) - New York Academy of Sciences Ser. . - New York Academy of Sciences Ser. .
Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- Introduction -- Chapter 1 Designing and Carrying Out a Statistical Study -- 1.1 A Small Example -- 1.2 Is Chance Responsible? The Foundation of Hypothesis Testing -- 1.3 A Major Example -- 1.4 Designing an Experiment -- 1.5 What to Measure-Central Location -- 1.6 What to Measure-Variability -- 1.7 What to Measure-Distance (Nearness) -- 1.8 Test Statistic -- 1.9 The Data -- 1.10 Variables and Their Flavors -- 1.11 Examining and Displaying the Data -- 1.12 Are we Sure we Made a Difference? -- Appendix: Historical Note -- 1.13 Exercises -- Chapter 2 Statistical Inference -- 2.1 Repeating the Experiment -- 2.2 How Many Reshuffles? -- 2.3 How Odd is Odd? -- 2.4 Statistical and Practical Significance -- 2.5 When to use Hypothesis Tests -- 2.6 Exercises -- Chapter 3 Displaying and Exploring Data -- 3.1 Bar Charts -- 3.2 Pie Charts -- 3.3 Misuse of Graphs -- 3.4 Indexing -- 3.5 Exercises -- Chapter 4 Probability -- 4.1 Mendel's Peas -- 4.2 Simple Probability -- 4.3 Random Variables and their Probability Distributions -- 4.4 The Normal Distribution -- 4.5 Exercises -- Chapter 5 Relationship between Two Categorical Variables -- 5.1 Two-Way Tables -- 5.2 Comparing Proportions -- 5.3 More Probability -- 5.4 From Conditional Probabilities to Bayesian Estimates -- 5.5 Independence -- 5.6 Exploratory Data Analysis (EDA) -- 5.7 Exercises -- Chapter 6 Surveys and Sampling -- 6.1 Simple Random Samples -- 6.2 Margin of Error: Sampling Distribution for a Proportion -- 6.3 Sampling Distribution for a Mean -- 6.4 A Shortcut-the Bootstrap -- 6.5 Beyond Simple Random Sampling -- 6.6 Absolute Versus Relative Sample Size -- 6.7 Exercises -- Chapter 7 Confidence Intervals -- 7.1 Point Estimates -- 7.2 Interval Estimates (Confidence Intervals) -- 7.3 Confidence Interval for a Mean. 7.4 Formula-Based Counterparts to the Bootstrap -- 7.5 Standard Error -- 7.6 Confidence Intervals for a Single Proportion -- 7.7 Confidence Interval for a Difference in Means -- 7.8 Confidence Interval for a Difference in Proportions -- 7.9 Recapping -- Appendix A: More on the Bootstrap -- Resampling Procedure-Parametric Bootstrap -- Formulas and the Parametric Bootstrap -- Appendix B: Alternative Populations -- Appendix C: Binomial Formula Procedure -- 7.10 Exercises -- Chapter 8 Hypothesis Tests -- 8.1 Review of Terminology -- 8.2 A-B Tests: The Two Sample Comparison -- 8.3 Comparing Two Means -- 8.4 Comparing Two Proportions -- 8.5 Formula-Based Alternative-t-Test for Means -- 8.6 The Null and Alternative Hypotheses -- 8.7 Paired Comparisons -- Appendix A: Confidence Intervals Versus Hypothesis Tests -- Confidence Interval -- Relationship Between the Hypothesis Test and the Confidence Interval -- Comment -- Appendix B: Formula-Based Variations of Two-Sample Tests -- Z-Test With Known Population Variance -- Pooled Versus Separate Variances -- Formula-Based Alternative: Z-Test for Proportions -- 8.8 Exercises -- Chapter 9 Hypothesis Testing-2 -- 9.1 A Single Proportion -- 9.2 A Single Mean -- 9.3 More Than Two Categories or Samples -- 9.4 Continuous Data -- 9.5 Goodness-of-Fit -- Appendix: Normal Approximation -- Hypothesis Test of a Single Proportion -- Confidence Interval for a Mean -- 9.6 Exercises -- Chapter 10 Correlation -- 10.1 Example: Delta Wire -- 10.2 Example: Cotton Dust and Lung Disease -- 10.3 The Vector Product and Sum Test -- 10.4 Correlation Coefficient -- 10.5 Other Forms of Association -- 10.6 Correlation is not Causation -- 10.7 Exercises -- Chapter 11 Regression -- 11.1 Finding the Regression Line by Eye -- 11.2 Finding the Regression Line by Minimizing Residuals -- 11.3 Linear Relationships -- 11.4 Inference for Regression. 11.5 Exercises -- Chapter 12 Analysis of Variance-ANOVA -- 12.1 Comparing More Than Two Groups: ANOVA -- 12.2 The Problem of Multiple Inference -- 12.3 A Single Test -- 12.4 Components of Variance -- 12.5 Two-Way ANOVA -- 12.6 Factorial Design -- 12.7 Exercises -- Chapter 13 Multiple Regression -- 13.1 Regression as Explanation -- 13.2 Simple Linear Regression-Explore the Data First -- 13.3 More Independent Variables -- 13.4 Model Assessment and Inference -- 13.5 Assumptions -- 13.6 Interaction, Again -- 13.7 Regression for Prediction -- 13.7.1 Example -- 13.8 Exercises -- Index -- End User License Agreement.
9781118881668
Electronic books.
Introductory Statistics and Analytics : A Resampling Perspective. - 1 online resource (309 pages) - New York Academy of Sciences Ser. . - New York Academy of Sciences Ser. .
Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- Introduction -- Chapter 1 Designing and Carrying Out a Statistical Study -- 1.1 A Small Example -- 1.2 Is Chance Responsible? The Foundation of Hypothesis Testing -- 1.3 A Major Example -- 1.4 Designing an Experiment -- 1.5 What to Measure-Central Location -- 1.6 What to Measure-Variability -- 1.7 What to Measure-Distance (Nearness) -- 1.8 Test Statistic -- 1.9 The Data -- 1.10 Variables and Their Flavors -- 1.11 Examining and Displaying the Data -- 1.12 Are we Sure we Made a Difference? -- Appendix: Historical Note -- 1.13 Exercises -- Chapter 2 Statistical Inference -- 2.1 Repeating the Experiment -- 2.2 How Many Reshuffles? -- 2.3 How Odd is Odd? -- 2.4 Statistical and Practical Significance -- 2.5 When to use Hypothesis Tests -- 2.6 Exercises -- Chapter 3 Displaying and Exploring Data -- 3.1 Bar Charts -- 3.2 Pie Charts -- 3.3 Misuse of Graphs -- 3.4 Indexing -- 3.5 Exercises -- Chapter 4 Probability -- 4.1 Mendel's Peas -- 4.2 Simple Probability -- 4.3 Random Variables and their Probability Distributions -- 4.4 The Normal Distribution -- 4.5 Exercises -- Chapter 5 Relationship between Two Categorical Variables -- 5.1 Two-Way Tables -- 5.2 Comparing Proportions -- 5.3 More Probability -- 5.4 From Conditional Probabilities to Bayesian Estimates -- 5.5 Independence -- 5.6 Exploratory Data Analysis (EDA) -- 5.7 Exercises -- Chapter 6 Surveys and Sampling -- 6.1 Simple Random Samples -- 6.2 Margin of Error: Sampling Distribution for a Proportion -- 6.3 Sampling Distribution for a Mean -- 6.4 A Shortcut-the Bootstrap -- 6.5 Beyond Simple Random Sampling -- 6.6 Absolute Versus Relative Sample Size -- 6.7 Exercises -- Chapter 7 Confidence Intervals -- 7.1 Point Estimates -- 7.2 Interval Estimates (Confidence Intervals) -- 7.3 Confidence Interval for a Mean. 7.4 Formula-Based Counterparts to the Bootstrap -- 7.5 Standard Error -- 7.6 Confidence Intervals for a Single Proportion -- 7.7 Confidence Interval for a Difference in Means -- 7.8 Confidence Interval for a Difference in Proportions -- 7.9 Recapping -- Appendix A: More on the Bootstrap -- Resampling Procedure-Parametric Bootstrap -- Formulas and the Parametric Bootstrap -- Appendix B: Alternative Populations -- Appendix C: Binomial Formula Procedure -- 7.10 Exercises -- Chapter 8 Hypothesis Tests -- 8.1 Review of Terminology -- 8.2 A-B Tests: The Two Sample Comparison -- 8.3 Comparing Two Means -- 8.4 Comparing Two Proportions -- 8.5 Formula-Based Alternative-t-Test for Means -- 8.6 The Null and Alternative Hypotheses -- 8.7 Paired Comparisons -- Appendix A: Confidence Intervals Versus Hypothesis Tests -- Confidence Interval -- Relationship Between the Hypothesis Test and the Confidence Interval -- Comment -- Appendix B: Formula-Based Variations of Two-Sample Tests -- Z-Test With Known Population Variance -- Pooled Versus Separate Variances -- Formula-Based Alternative: Z-Test for Proportions -- 8.8 Exercises -- Chapter 9 Hypothesis Testing-2 -- 9.1 A Single Proportion -- 9.2 A Single Mean -- 9.3 More Than Two Categories or Samples -- 9.4 Continuous Data -- 9.5 Goodness-of-Fit -- Appendix: Normal Approximation -- Hypothesis Test of a Single Proportion -- Confidence Interval for a Mean -- 9.6 Exercises -- Chapter 10 Correlation -- 10.1 Example: Delta Wire -- 10.2 Example: Cotton Dust and Lung Disease -- 10.3 The Vector Product and Sum Test -- 10.4 Correlation Coefficient -- 10.5 Other Forms of Association -- 10.6 Correlation is not Causation -- 10.7 Exercises -- Chapter 11 Regression -- 11.1 Finding the Regression Line by Eye -- 11.2 Finding the Regression Line by Minimizing Residuals -- 11.3 Linear Relationships -- 11.4 Inference for Regression. 11.5 Exercises -- Chapter 12 Analysis of Variance-ANOVA -- 12.1 Comparing More Than Two Groups: ANOVA -- 12.2 The Problem of Multiple Inference -- 12.3 A Single Test -- 12.4 Components of Variance -- 12.5 Two-Way ANOVA -- 12.6 Factorial Design -- 12.7 Exercises -- Chapter 13 Multiple Regression -- 13.1 Regression as Explanation -- 13.2 Simple Linear Regression-Explore the Data First -- 13.3 More Independent Variables -- 13.4 Model Assessment and Inference -- 13.5 Assumptions -- 13.6 Interaction, Again -- 13.7 Regression for Prediction -- 13.7.1 Example -- 13.8 Exercises -- Index -- End User License Agreement.
9781118881668
Electronic books.