Common Errors in Statistics (And How to Avoid Them) by Good, Phillip I. -- Read -- Imperial Library of Trantor

Index

Cover Title page Copyright page Preface Part I: FOUNDATIONS

Chapter 1 Sources of Error

PRESCRIPTION FUNDAMENTAL CONCEPTS SURVEYS AND LONG-TERM STUDIES AD-HOC, POST-HOC HYPOTHESES TO LEARN MORE

Chapter 2 Hypotheses: The Why of Your Research

PRESCRIPTION WHAT IS A HYPOTHESIS? HOW PRECISE MUST A HYPOTHESIS BE? FOUND DATA NULL OR NIL HYPOTHESIS NEYMAN–PEARSON THEORY DEDUCTION AND INDUCTION LOSSES DECISIONS TO LEARN MORE

Chapter 3 Collecting Data

PREPARATION RESPONSE VARIABLES DETERMINING SAMPLE SIZE FUNDAMENTAL ASSUMPTIONS EXPERIMENTAL DESIGN FOUR GUIDELINES ARE EXPERIMENTS REALLY NECESSARY? TO LEARN MORE

Part II: STATISTICAL ANALYSIS

Chapter 4 Data Quality Assessment

OBJECTIVES REVIEW THE SAMPLING DESIGN DATA REVIEW TO LEARN MORE

Chapter 5 Estimation

PREVENTION DESIRABLE AND NOT-SO-DESIRABLE ESTIMATORS INTERVAL ESTIMATES IMPROVED RESULTS SUMMARY TO LEARN MORE

Chapter 6 Testing Hypotheses: Choosing a Test Statistic

FIRST STEPS TEST ASSUMPTIONS BINOMIAL TRIALS CATEGORICAL DATA TIME-TO-EVENT DATA (SURVIVAL ANALYSIS) COMPARING THE MEANS OF TWO SETS OF MEASUREMENTS DO NOT LET YOUR SOFTWARE DO YOUR THINKING FOR YOU COMPARING VARIANCES COMPARING THE MEANS OF K SAMPLES HIGHER-ORDER EXPERIMENTAL DESIGNS INFERIOR TESTS MULTIPLE TESTS BEFORE YOU DRAW CONCLUSIONS INDUCTION SUMMARY TO LEARN MORE

Chapter 7 Strengths and Limitations of Some Miscellaneous Statistical Procedures

NONRANDOM SAMPLES MODERN STATISTICAL METHODS BOOTSTRAP BAYESIAN METHODOLOGY META-ANALYSIS PERMUTATION TESTS TO LEARN MORE

Chapter 8 Reporting Your Results

FUNDAMENTALS DESCRIPTIVE STATISTICS ORDINAL DATA TABLES STANDARD ERROR P-VALUES CONFIDENCE INTERVALS RECOGNIZING AND REPORTING BIASES REPORTING POWER DRAWING CONCLUSIONS PUBLISHING STATISTICAL THEORY A SLIPPERY SLOPE SUMMARY TO LEARN MORE

Chapter 9 Interpreting Reports

WITH A GRAIN OF SALT THE AUTHORS COST–BENEFIT ANALYSIS THE SAMPLES AGGREGATING DATA EXPERIMENTAL DESIGN DESCRIPTIVE STATISTICS THE ANALYSIS CORRELATION AND REGRESSION GRAPHICS CONCLUSIONS RATES AND PERCENTAGES INTERPRETING COMPUTER PRINTOUTS SUMMARY TO LEARN MORE

Chapter 10 Graphics

IS A GRAPH REALLY NECESSARY? KISS THE SOCCER DATA FIVE RULES FOR AVOIDING BAD GRAPHICS ONE RULE FOR CORRECT USAGE OF THREE-DIMENSIONAL GRAPHICS THE MISUNDERSTOOD AND MALIGNED PIE CHART TWO RULES FOR EFFECTIVE DISPLAY OF SUBGROUP INFORMATION TWO RULES FOR TEXT ELEMENTS IN GRAPHICS MULTIDIMENSIONAL DISPLAYS CHOOSING EFFECTIVE DISPLAY ELEMENTS ORAL PRESENTATIONS SUMMARY TO LEARN MORE

Part III: BUILDING A MODEL

Chapter 11 Univariate Regression

MODEL SELECTION STRATIFICATION FURTHER CONSIDERATIONS SUMMARY TO LEARN MORE

Chapter 12 Alternate Methods of Regression

LINEAR VERSUS NONLINEAR REGRESSION LEAST-ABSOLUTE-DEVIATION REGRESSION QUANTILE REGRESSION SURVIVAL ANALYSIS THE ECOLOGICAL FALLACY NONSENSE REGRESSION REPORTING THE RESULTS SUMMARY TO LEARN MORE

Chapter 13 Multivariable Regression

CAVEATS DYNAMIC MODELS FACTOR ANALYSIS REPORTING YOUR RESULTS A CONJECTURE DECISION TREES BUILDING A SUCCESSFUL MODEL TO LEARN MORE

Chapter 14 Modeling Counts and Correlated Data

COUNTS BINOMIAL OUTCOMES COMMON SOURCES OF ERROR PANEL DATA FIXED- AND RANDOM-EFFECTS MODELS POPULATION-AVERAGED GENERALIZED ESTIMATING EQUATION MODELS (GEEs) SUBJECT-SPECIFIC OR POPULATION-AVERAGED? VARIANCE ESTIMATION QUICK REFERENCE FOR POPULAR PANEL ESTIMATORS TO LEARN MORE

Chapter 15 Validation

OBJECTIVES METHODS OF VALIDATION MEASURES OF PREDICTIVE SUCCESS TO LEARN MORE

Glossary Bibliography Author Index Subject Index