“The best feature of the book is that it covers the analytical processes left out of most research and statistics courses. It is very practical and most importantly, easy to read and understand. I have students continually tell me that they still have their ‘Statistical Consultant’ and they use it all the time.” - Barry B. Shultz, The University of Utah
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.
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.