» Intermediate Statistics For Dummies (For Dummies (Math & Science))

Intermediate Statistics For Dummies (For Dummies (Math & Science)) Reviews

Customer Rating:
Summary: Big picture without sacrificing depth + careful explanation of essential statistical ideas
Comment: I read many traditional books in statistics, to include intro and advanced ones. Most of them either focus too much on the algebraic details with almost no discussion of the essential statistical concepts or they focus too much on abstract theorizing with little technical and practical content.

Prof. Rumsey's book on the other hand, does a great job keeping the discussion to an easy to follow level of understanding without sacrificing important details and the complexity and subtleties that essential statistical concepts and techniques require (e.g., testing models vis-à-vis hypothesis testing, confidence intervals, multiple regressions, nonparametric methods, discussion of Simpson's paradox).

This book can be a good supplemental reading for those students from humanities, the social and behavioral sciences, as well as anyone interested in having a quick review of the fundamentals of stats plus a good walk through of the highly demanded (and often misunderstood and abused) statistical tools for everyday practice in applied fields.

I recommend this book, and I wish other statisticians could explain as well as Prof. Rumsey does.

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Customer Rating:
Summary: OK if you want to learn how to use statistical tests, inadequate if you want to LEARN statistics
Comment: As someone who has taught a college level course in basics statistics for over a quarter century, I am both intrigued and disturbed by the phrase "Intermediate Statistics." In general, there is basic and advanced statistics, so my first thought is that to create the intermediate category, you must reduce the coverage in the basic and advanced levels to make room or simply repeat the last part of the basic section and the first part of the advanced section. I am intrigued because if it is properly done, a section called intermediate statistics could be used to fill holes otherwise missed.
In terms of content, I really cannot argue with the "intermediate" descriptor. The coverage is:

*) The fundamentals of statistical models and hypothesis testing.
*) Using linear and nonlinear regression to make predictions based on data.
*) Using one and two-way analysis of variance (ANOVA)
*) Using the chi-square test to test associations, independence and goodness-of-fit
*) Using nonparametric statistics such as the sign, signed rank, rank sum, Kruskal-Wallis, Wilcox and Spearman's rank tests.

When I teach the basic statistics course, these are subjects that tend to get left out, in general I never get to two-way ANOVA, goodness-of-fit and nonparametric statistics.
The problem that I have with this book, and it is a major one, is that there are few formulas and no worked examples. A brief description of the statistical test is given with a set of sample data. The author then crunches the data through Minitab and reports the results in an output table. In my experience, students really do not learn how to do the statistical tests or what they are really measuring by simply having results listed. They must see the formulas worked through and physically work through them at least once. Mathematics and statistics is very much a participation sport, and there is very little participation here.

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Customer Rating:
Summary: Excellent for reviewers and newbies
Comment: I did not find any use for my college statistics when I started working (at least for my function), but just recently, I had to relearn, what I've forgotten to keep pace with the demands of my job. This book is heavenly! Whether you're someone looking for a refresher course without having to pay huge sums to pick-up on stuff you know you've already learned or someone who wants the basics of statistics, this is the book for you.

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Customer Rating:
Summary: A Good Sequel to Statistics for Dummies
Comment: I'm glad the author has provided us with a good sequel to her previous "for dummies" books. This book addresses "intermediate" topics like linear and non-linear regression, ANOVA, and non-parametric tests. Also, the author uses again her successful formula of providing useful tips and hints at the end of the book (see Part VI).

Book Contents:

Part I: Data Analysis and Model-Building Basics.
Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis.
Chapter 2: Sorting through Statistical Techniques.
Chapter 3: Building Confidence and Testing Models.

Part II: Making Predictions by Using Regression.
Chapter 4: Getting in Line with Simple Linear Regression.
Chapter 5: When Two Variables Are Better than One: Multiple Regression.
Chapter 6: One Step Forward and Two Steps Back: Regression Model Selection.
Chapter 7: When Data Throws You a Curve: Using Nonlinear Regression.
Chapter 8: Yes, No, Maybe So: Making Predictions By Using Logistic Regression.

Part III: Comparing Many Means with ANOVA.
Chapter 9: Going One-Way with Analysis of Variance.
Chapter 10: Pairing Things Down with Multiple Comparisons.
Chapter 11: Getting a Little Interaction with Two-Way ANOVA.
Chapter 12: Rock My World: Relating Regression to ANOVA.

Part IV: Building Strong Connections with Chi-Square Tests.
Chapter 13: Forming Associations with Two-Way Tables.
Chapter 14: Being Independent Enough for the Chi-Square Test.
Chapter 15: Using Chi-Square Tests for Goodness-of-Fit (Your Data, Not Your Jeans).

Part V: Rebels without a Distribution.
Chapter 16: Going Nonparametric.
Chapter 17: The Sign Test and Signed Rank Test.
Chapter 18: Pulling Rank with the Rank Sum Test.
Chapter 19: Do the Kruskal-Wallis and Rank the Sums with Wilcox.
Chapter 20: Pointing Out Correlations with Spearman's Rank.

Part VI: The Part of Tens.
Chapter 21: Ten Errors in Statistical Conclusions.
Chapter 22: Ten Practice Problems.
Appendix: Tables for Your Reference.
Index.

In short, a good introductory book at a fair price.

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Customer Rating:
Summary: Statistics not for Dummies
Comment: I'm not familiar with Rumsy's "Statistics for Dummies," but this book is a nice overview of a second statistics course. The chapters on multiple regression techniques are especially good. The writing style is clear. Negatives: Only Minitab is used to illustrate data analysis. No SPSS. There might have been more data sets for the various techniques.

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