Common Errors in Statistics (and How to Avoid Them). (2012)

• Record Type: Book
• Further Information: Note: Phillip I. Good, James W. Hardin.
• Authors: Good, Phillip I; Hardin, James W
• Contents: Preface xi PART I FOUNDATIONS 1 1. Sources of Error 3 ; Prescription 4; Fundamental Concepts 5; Surveys and Long-Term Studies 9; Ad-Hoc, Post-Hoc Hypotheses 9; To Learn More 13 2. Hypotheses: The Why of Your Research 15 ; Prescription 15; What Is a Hypothesis? 16; How Precise Must a Hypothesis Be? 17; Found Data 18; Null or Nil Hypothesis 19; Neyman–Pearson Theory 20; Deduction and Induction 25; Losses 26; Decisions 27; To Learn More 28 3. Collecting Data 31 ; Preparation 31; Response Variables 32; Determining Sample Size 37; Fundamental Assumptions 46; Experimental Design 47; Four Guidelines 49; Are Experiments Really Necessary? 53; To Learn More 54 PART II STATISTICAL ANALYSIS 57 4. Data Quality Assessment 59 ; Objectives 60; Review the Sampling Design 60; Data Review 62; To Learn More 63 5. Estimation 65 ; Prevention 65; Desirable and Not-So-Desirable Estimators 68; Interval Estimates 72; Improved Results 77; Summary 78; To Learn More 78 6. Testing Hypotheses: Choosing a Test Statistic 79 ; First Steps 80; Test Assumptions 82; Binomial Trials 84; Categorical Data 85; Time-To-Event Data (Survival Analysis) 86; Comparing the Means of Two Sets of Measurements 90; Do Not Let Your Software Do Your Thinking For You 99; Comparing Variances 100; Comparing the Means of K Samples 105; Higher-Order Experimental Designs 108; Inferior Tests 113; Multiple Tests 114; Before You Draw Conclusions 115; Induction 116; Summary 117; To Learn More 117 7. Strengths and Limitations of Some Miscellaneous Statistical Procedures 119 ; Nonrandom Samples 119; Modern Statistical Methods 120; Bootstrap 121; Bayesian Methodology 123; Meta-Analysis 131; Permutation Tests 135; To Learn More 137 8. Reporting Your Results 139 ; Fundamentals 139; Descriptive Statistics 144; Ordinal Data 149; Tables 149; Standard Error 151; p -Values 155; Confidence Intervals 156; Recognizing and Reporting Biases 158; Reporting Power 160; Drawing Conclusions 160; Publishing Statistical Theory 162; A Slippery Slope 162; Summary 163; To Learn More 163 9. Interpreting Reports 165 ; With a Grain of Salt 165; The Authors 166; Cost–Benefit Analysis 167; The Samples 167; Aggregating Data 168; Experimental Design 168; Descriptive Statistics 169; The Analysis 169; Correlation and Regression 171; Graphics 171; Conclusions 172; Rates and Percentages 174; Interpreting Computer Printouts 175; Summary 178; To Learn More 178 10. Graphics 181 ; Is a Graph Really Necessary? 182; KISS 182; The Soccer Data 182; Five Rules for Avoiding Bad Graphics 183; One Rule for Correct Usage of Three-Dimensional Graphics 194; The Misunderstood and Maligned Pie Chart 196; Two Rules for Effective Display of Subgroup Information 198; Two Rules for Text Elements in Graphics 201; Multidimensional Displays 203; Choosing Effective Display Elements 209; Oral Presentations 209; Summary 210; To Learn More 211 PART III BUILDING A MODEL 213 11. Univariate Regression 215 ; Model Selection 215; Stratification 222; Further Considerations 226; Summary 233; To Learn More 234 12. Alternate Methods of Regression 237 ; Linear Versus Nonlinear Regression 238; Least-Absolute-Deviation Regression 238; Quantile Regression 243; Survival Analysis 245; The Ecological Fallacy 246; Nonsense Regression 248; Reporting the Results 248; Summary 248; To Learn More 249 13. Multivariable Regression 251 ; Caveats 251; Dynamic Models 256; Factor Analysis 256; Reporting Your Results 258; A Conjecture 260; Decision Trees 261; Building a Successful Model 264; To Learn More 265 14. Modeling Counts and Correlated Data 267 ; Counts 268; Binomial Outcomes 268; Common Sources of Error 269; Panel Data 270; Fixed- and Random-Effects Models 270; Population-Averaged Generalized Estimating Equation Models (GEEs) 271; Subject-Specific or Population-Averaged? 272; Variance Estimation 272; Quick Reference for Popular Panel Estimators 273; To Learn More 275 15. Validation 277 ; Objectives 277; Methods of Validation 278; Measures of Predictive Success 283; To Learn More 285 Glossary 287 Bibliography 291 Author Index 319 Subject Index 329
• Edition: 4th
• Publisher Details: Wiley
• Publication Date: 2012
• Extent: 1 online resource (352 pages)
• Languages: English
• ISBNs: 9781118360118
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.