Your Statistical Consultant
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Your Statistical Consultant
Answers to Your Data Analysis Questions

Second Edition


© 2013 | 384 pages | SAGE Publications, Inc
How do you bridge the gap between what you learned in your statistics course and the questions you want to answer in your real-world research? Oriented towards distinct questions in a “How do I?” or “When should I?” format, Your Statistical Consultant is the equivalent of the expert colleague down the hall who fields questions about describing, explaining, and making recommendations regarding thorny or confusing statistical issues. The book serves as a compendium of statistical knowledge, both theoretical and applied, that addresses the questions most frequently asked by students, researchers and instructors. Written to be responsive to a wide range of inquiries and levels of expertise, the book is flexibly organized so readers can either read it sequentially or turn directly to the sections that correspond to their concerns.
 
Chapter 1. Getting Started With Statistical Analysis: Where Do I Obtain Data and How Do I Prepare Data for Statistical Analysis?
 
Chapter 2. How Do I Examine Data Prior to Analysis?
 
Chapter 3. Traditional Approaches to Statistical Analysis and the Logic of Statistical Inference
 
Chapter 4. Rethinking Traditional Paradigms: Power, Effect Size, and Hypothesis Testing Alternatives
 
Chapter 5. What Are the Assumptions of Statistical Testing?
 
Chapter 6. An Introduction to Statistical Models: Explaining Relationship Patterns
 
Chapter 7. How Do I Select the Appropriate Statistical Test?
 
Chapter 8. How Do I Deal With Non-Normality, Missing Values, and Outliers?
 
Chapter 9. Types of Variables and Their Treatment in Statistical Analysis
 
Chapter 10. Questions about Analysis of Variance
 
Chapter 11. Questions abuot Multiple Regression Analysis
 
Chapter 12. The Bigger Picture
Key features

NEW TO THIS EDITION:

  • References to online resources and meth­ods, including statistical analysis programs such as Stata, SAS, and SPSS, have expanded.
  • Updates to reflect current thinking about null hypothesis significance testing and alternatives have been made.
  • Numerous links to free software that addresses such issues as identifying and graphing interaction effects, conducting power analy­ses, and correcting for missing values using multiple imputation methods are included.
  • An entirely new chapter on statistical modeling has been added.
  • Updates to address current thinking about use of non-parametric methods, missing data analysis and imputation, meta-analysis, confidence intervals and effect size have been made.
  • Updates to address significant changes in the way statistics is conceptualized, taught, and applied in current practice have been made.

 KEY FEATURES:

  • The Second Edition has been significantly expanded with user-friendly illustrations and visual examples.
  • The authors discuss the issues that pertain to a range of statistical questions and controversies, reveal divergent perspectives on these issues, and offer practical advice and examples for conducting statistical analyses that reflect their interpretation of the consensual wisdom of the field.
  • Chapter headings are followed by detailed answers to questions, including conceptual explanations and clarifications of the use and nuances of a particular technique or issue.
  • Examples and opinions of contemporary statistical experts are cited throughout the book.

Those readers who are familiar with the original publication of this book will observe that this revised edition is significantly expanded. We have added more user-friendly illustrations and examples and updated our references and recommendations for supplementary readings and resource materials. For instance, we have provided tables and guidelines for using basic bivariate procedures, selecting appropriate planned comparisons and post-hoc analyses, and selecting appropriate missing data procedures. We have augmented our discussions of the visual examination and presentation of data, missing data and related data distribution problems, meta-analysis, multiple regression, and measures of substantive (clinical) significance. We have incorporated new topics such as secondary data analysis, bootstrapping, mediator and moderator variables, and modern robust statistics. Predictably, reference to online resources and methods has expanded, including statistical analysis programs such as Stata, SAS, and SPSS. Perhaps most significantly, we have attempted to clarify changes in the way that statistics is currently being taught in more progressive academic programs and institutions. This includes giving more than lip service to the limitations of traditional null hypothesis significance testing (NHST), a controversy that we introduced previously. One indicator of taking these changes seriously is the inclusion of a new chapter on statistical modeling. Finally, since the original publication of Your Statistical Consultant, a considerable body of new literature has appeared addressing the use of common guidelines for statistical practice. Much of this literature suggests that the assumptions and rules of thumb that often guide analyses are unwarranted and should be relegated to the bin of statistical myths. We have referenced this literature heavily, and when necessary, have modified our own position to include the current state of thinking about these issues.


Sample Materials & Chapters

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ISBN: 9781412997591

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