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Common errors in statistics (and how to avoid them)

Author: Good, Phillip I. ; Hardin, JamesPublisher: Wiley, 2006.Edition: 2nd ed.Language: EnglishDescription: 254 p. : Graphs ; 20 cm.ISBN: 0471794317Type of document: BookBibliography/Index: Includes bibliographical references and index
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Item type Current location Collection Call number Status Date due Barcode Item holds
Book Europe Campus
Main Collection
Print QA276 .G66 2006
(Browse shelf)
001179047
Available 001179047
Total holds: 0

Includes bibliographical references and index

Digitized

Common Errors in Statistics (and How to Avoid Them) Contents Preface ix PART I FOUNDATIONS 1. Sources of Error Prescription Fundamental Concepts Ad Hoc, Post Hoc Hypotheses 2. Hypotheses: The Why of Your Research Prescription What Is a Hypothesis? How precise must a hypothesis be? Found Data Null hypothesis Neyman--Pearson Theory Deduction and Induction Losses Decisions To Learn More 3. Collecting Data Preparation Measuring Devices Determining Sample Size Fundamental Assumptions Experimental Design Four Guidelines 1 3 4 4 7 13 13 13 14 16 16 17 21 22 24 25 27 27 28 31 36 38 39 Are Experiments Really Necessary? To Learn More 42 42 PART II HYPOTHESIS TESTING AND ESTIMATION 4. Estimation Prevention Desirable and Not-So-Desirable Estimators Interval Estimates Improved Results Summary To Learn More 5. Testing Hypotheses: Choosing a Test Statistic Comparing Means of Two Populations Comparing Variances Comparing the Means of K Samples Higher-Order Experimental Designs Contingency Tables Inferior Tests Multiple Tests Before You Draw Conclusions Summary To Learn More 6. Strengths and Limitations of Some Miscellaneous Statistical Procedures Bootstrap Bayesian Methodology Meta-Analysis Permutation Tests To Learn More 7. Reporting Your Results Fundamentals Tables Standard Error p-Values Confidence Intervals Recognizing and Reporting Biases Reporting Power Drawing Conclusions 45 47 47 47 51 55 56 56 57 59 67 71 73 79 80 81 81 84 84 87 88 89 96 99 99 101 101 104 105 110 111 113 115 115 Summary To Learn More 8. Interpreting Reports With A Grain of Salt Rates and Percentages Interpreting Computer Printouts 9. Graphics The Soccer Data Five Rules for Avoiding Bad Graphics One Rule for Correct Usage of Three-Dimensional Graphics The Misunderstood Pie Chart Two Rules for Effective Display of Subgroup Information Two Rules for Text Elements in Graphics Multidimensional Displays Choosing Graphical Displays Summary To Learn More 116 116 119 119 122 123 125 125 126 133 135 136 140 141 143 143 144 PART III BUILDING A MODEL 10. Univariate Regression Model Selection Estimating Coefficients Further Considerations Summary To Learn More 11. Alternate Methods of Regression Linear vs. Nonlinear Regression Least Absolute Deviation Regression Errors-in-Variables Regression Quantile Regression The Ecological Fallacy Nonsense Regression Summary To Learn More 12. Multivariable Regression Caveats Factor Analysis General Linearized Models Reporting Your Results 145 147 147 155 157 160 162 163 164 164 165 169 170 172 172 172 175 175 178 178 181 A Conjecture Decision Trees Building a Successful Model To Learn More 13. Validation Methods of Validation Measures of Predictive Success Long-Term Stability To Learn More Appendix A Appendix B Glossary, Grouped by Related but Distinct Terms Bibliography Author Index Subject Index 182 183 185 186 187 188 191 193 194 195 205 219 223 243 249

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