Your Statistical Consultant
Answers to Your Data Analysis Questions
- Rae R. Newton - Fielding Graduate University, USA
- Kjell Erik Rudestam - Fielding Graduate University, USA
Quantitative Methods
It covers all the basics that we need to cover in the course and does so in an easy to read format.
it covers what i need to cover in the best manor, i am doing IT research and needed a text that could break down Quan research best.
Ordered for Library.
I will use it as a book to consult. Also, I will recommend to my students, specially those in dissertation.
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.
