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Statistics, by William Hays
Ebook Statistics, by William Hays
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Statistics by Hays,William. [1994,5th Edition.] Hardcover
- Sales Rank: #809331 in Books
- Published on: 1994-01-02
- Original language: English
- Number of items: 1
- Dimensions: 9.54" h x 1.76" w x 7.65" l, 3.95 pounds
- Binding: Hardcover
- 1136 pages
Review
Preface. Introduction. Elementary Probability Theory. Frequency and Probability Distributions. A Discrete Random Variable: The Binomial. Central Tendency and Variability. Sampling Distributions and Point Estimation. Normal Population and Sampling Distributions. Hypothesis Testing. Inferences About Population Means. The Chi-Square and F Distributions. The General Linear Model and the Analysis of Variance. Comparisons Among Means. Factorial Designs and Higher-Order Analysis of Variance. Analysis of Variance Models II and III: Random Effects and Mixed Models. Problems in Regression and Correlation. Partial and Multiple Regression. Further Topics in Regression. The Analysis of Covariance. Analyzing Qualitative Data: Chi-Square Tests. Terms You Should Know. Practice Exercises. Exercises. Appendix A: Rules of Summation. Appendix B: The Algebra of Expectations. Appendix C: Joint Random Variables and Linear Combinations. Appendix D: Some Principles and Applications of Matrix Algebra. Appendix E: Sets and Functions. Appendix F: Tables. Appendix G: Solutions to Selected Exercises References and Suggestions for Further Reading. Glossary of Symbols. Index.
About the Author
Kim Hays teaches in the Department of Social Psychology at the University of Z?rich. As executive director of the non-profit Action for Children's Television from 1979 to 1983, she edited "TV, Science, and Kids: Teaching Our Children to Question".
Most helpful customer reviews
16 of 18 people found the following review helpful.
Invaluable reference; Not for pleasure reading
By N. Schweitzer
Hays's text is not meant for everyone; hence the mixed reviews. It was not the primary source from which I gained my knowledge of statistics; however it serves as an invaluable reference. Unlike some of the other reviewers, I had little difficulty understanding the material as Hays presented it. Some of the criticisms are points well-taken; for example a lack of annotation in the power tables at the end of the book (which are still decipherable if you know what you're looking at).
This text is for the mathematically inclined-it is not a "how-to" book, rather a "why" book that thoroughly explains the theory behind a variety of popular inferential techniques. If this is the sort of knowledge you are seeking, Hays is the book for you. If you are interested in a more "common-sense" or applied approach, perhaps you should look elsewhere.
5 of 5 people found the following review helpful.
Excellent if you are not a minor in the field anymore
By C. H. van Wijk
'Hays' is truely a classic; one of the few books that will stay close at hand as long as I work (as an applied social scientist). It did not teach me statistics, but since then the book has helped me many times to understand statistics a bit better. Don't use it as an introduction to the field. Reach for this book every time you want to know more about "why so" after you have learned "how to do".
22 of 25 people found the following review helpful.
Useful as a reference, not as a book to learn from
By Words Dance Before my Eyes in a Meaningless Procession
I agree with Van Denburg's evaluation.
I am a graduate student in Psychology, and I find the Hays text mostly illegible. His prose is dense and his explanations rely very heavily on mathematical formulae instead of real-world or logical/verbal descriptions. Furthermore, he falls into the typical "math textbook" pit of giving solutions to only the example problems that are exceptions to what one would usually encounter.
This is especially bad considering that my concentration specializes in statistical inference, and I've studied mathematics through differential equations (including linear algebra, multivariate).
Worse, Hays has a tendency to use different symbols to represent variables compared to other statistical texts (and in some cases, the rest of the world!)
Lastly, the tables that Hays has in the back of his book are not notated. He does not explain what each table represents, or what the x or y axis are. In one case, he has two entries for each lookup in the ANOVA Power of Association (omega squared) (Table XII, page 1032). Nowhere in the table does it mention what these two values are for.
It is only in one paragraph 600 pages earlier, that he explains that the two values are for alpha=0.05 and 0.01 and that n must be equal for both groups!! (page 410)
I am currently relying on several other texts to understand statistics for the social/behaviourial sciences. If you are extremely comfortable with mathematics to describe your behaviourial tests, you may find this book valuable. If you prefer a more descriptive approach, I suggest another one.
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