Common Errors in Statistics

Name: Common Errors in Statistics
Price: 18.3 USD
Availability: InStock
ISBN: 9780471794318

ISBN-10: 0471794317

ISBN-13: 9780471794318

Edition: 2nd 2006 (Revised)

Authors: Phillip I. Good, James W. Hardin

List price: $84.95

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Description:

Common Errors is consistently coherent and provides a consistent level throughout.The Second Edition elaborates ona few key topics such as testing hypotheses (two-way designs) and multivariate regression (nonuniqueness and indicator variables).

Book details

List price: $84.95
Edition: 2nd
Copyright year: 2006
Publisher: John Wiley & Sons, Incorporated
Publication date: 4/28/2006
Binding: Paperback
Pages: 272
Size: 6.00" wide x 8.75" long x 0.75" tall
Weight: 0.946
Language: English



Preface



Foundations.



Sources of Error


Prescription


Fundamental Concepts


Ad Hoc, Post Hoc Hypotheses



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



Collecting Data


Preparation


Measuring Devices


Determining Sample Size


Fundamental Assumptions


Experimental Design


Four Guidelines


Are Experiments Really Necessary?


To Learn More



Hypothesis Testing And Estimation.



Estimation


Prevention


Desirable and Not-So-Desirable Estimators


Interval Estimates


Improved Results


Summary


To Learn More



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



Strengths and Limitations of Some Miscellaneous Statistical Procedures


Bootstrap


Bayesian Methodology


Meta-Analysis


Permutation Tests


To Learn More



Reporting Your Results


Fundamentals


Tables


Standard Error


p-Values


Confidence Intervals


Recognizing and Reporting Biases


Reporting Power


Drawing Conclusions


Summary


To Learn More



Interpreting Reports


With A Grain of Salt


Rates and Percentages


Interpreting Computer Printouts



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



Building A Model.



Univariate Regression


Model Selection


Estimating Coefficients


Further Considerations


Summary


To Learn More



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



Multivariable Regression


Caveats


Factor Analysis


General Linearized Models


Reporting Your Results


A Conjecture


Decision Trees


Building a Successful Model


To Learn More



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.