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eBook Handbook of Parametric and Nonparametric Statistical Procedures: Fourth Edition ePub

by David J. Sheskin

eBook Handbook of Parametric and Nonparametric Statistical Procedures: Fourth Edition ePub
Author: David J. Sheskin
Language: English
ISBN: 1584888148
ISBN13: 978-1584888147
Publisher: Chapman and Hall/CRC; 4 edition (January 19, 2007)
Pages: 1772
Category: Mathematics
Subcategory: Science
Rating: 4.4
Votes: 156
Formats: lrf lit lrf txt
ePub file: 1432 kb
Fb2 file: 1617 kb

Format: HardcoverVerified Purchase.

I also recommend it for teachers who will find a lot of good examples they can use within their courses. Format: HardcoverVerified Purchase.

Parametric versus Nonparametric Inferential Statistical Tests. A. Meta-analytic procedures. Guidelines and Decision Tables for Selecting the Appropriate Statistical Procedure. Inferential Statistical Tests Employed with a Single Sample

Parametric versus Nonparametric Inferential Statistical Tests. Selection of the Appropriate Statistical Procedure. Outline of Inferential Statistical Tests and Measures of ion. I. Inferential statistical tests employed with a single sample. Inferential statistical tests employed with interval/ratio data. Test 1: The Single-Sample z Test.

Thorough - Up-To-DateWith details of more than 100 statistical procedures, the Handbook offers unparalleled coverage of modern statistical methods. You get in-depth discussion of both practical and theoretical issues, many of which are not addressed in conventional statistics books.

Now author David Sheskin has gone several steps further and added even more tests, more examples, and more background information-more than 200 pages of new material.

Vlll Handbook of Parametric andNonparametric Statistical Procedures of ion. The general label test is employed for all procedures described in the book (. inferential tests as well as measures of ion).

Handbook of Parametric and Nonparametric Statistical Procedures. Test 7: The Kolmogorov-Smirnov Goodness-of-Fit Test for a Single Sample

Handbook of Parametric and Nonparametric Statistical Procedures. Test 7: The Kolmogorov-Smirnov Goodness-of-Fit Test for a Single Sample. Test and/or Related Tests 1. Comparisons involving individual cells when k 2 2. The analysis of standardized residuals 3. The correction for continuity for the chi-square goodness-of-fit test 4. Computation of a confidence interval for the chi-square goodness-of-fit test/confidence interval for a population proportion 5. Brief discussion of the ζ test for a population proportion.

The book also discusses both theoretical and practical statistical topics, such as experimental design, experimental control, and statistical analysis.

all procedures are presented in detail. it is a reference book par excellence.

Chapman and Hall/CRC Published April 27, 2011 Reference - 1926 Pages - 128 B/W Illustrations ISBN 9781439858011 - CAT K12706. all procedures are presented in detail. I also recommend it for teachers who will find a lot of good examples they can use within their courses.

In Proceedings of the 4 th International Conference on Artificial Neural Nets and Genetic Algorithms, pages 1–11, 1999.

Handbook of Parametric and Nonparametric Statistical Proce- dures. ISBN: 1-5848-8133-X, 978-1-58488-133-9, 1-5848-8440-1, 978-1-58488-440-8, 978-1-58488-814-7. In Proceedings of the 4 th International Conference on Artificial Neural Nets and Genetic Algorithms, pages 1–11, 1999.

With more than 500 pages of new material, the Handbook of Parametric and Nonparametric Statistical Procedures, Fourth Edition carries on the esteemed tradition of the previous editions, providing up-to-date, in-depth coverage of now more than 160 statistical procedures. The book also discusses both theoretical and practical statistical topics, such as experimental design, experimental control, and statistical analysis.New to the Fourth EditionMultivariate statistics including matrix algebra, multiple regression, Hotellings T2, MANOVA, MANCOVA, discriminant function analysis, canonical correlation, logistic regression, and principal components/factor analysisClinical trials, survival analysis, tests of equivalence, analysis of censored data, and analytical procedures for crossover designRegression diagnostics that include the Durbin-Watson testLog-linear analysis of contingency tables, Mantel-Haenszel analysis of multiple 2 × 2 contingency tables, trend analysis, and analysis of variance for a Latin square designLevene and Brown-Forsythe tests for evaluating homogeneity of variance, the Jarque-Bera test of normality, and the extreme studentized deviate test for identifying outliersConfidence intervals for computing the population median and the difference between two population mediansThe relationship between exponential and Poisson distribution Eliminating the need to search across numerous books, this handbook provides you with everything you need to know about parametric and nonparametric statistical procedures. It helps you choose the best test for your data, interpret the results, and better evaluate the research of others.
riki
This is my second purchase of this book, with the first purchase for the prior edition - I find it so useful as a reference that I have one in the office and one at home. This text is excellent for reminding one which null hypothesis, exactly, one is testing, and is clear on the assumptions beibg made (e.g. iid observations). It is particularly useful in refreshing knowledge of tests, and explaining various modifications to statistical tests. As with the previous version, each test is shown with an example set of data and associated hypothesis. The book does assume some statistics knowledge, and would be suitable as a reference statistics text for computer scientists and operations researchers, as well as applied statisticians. Social scientists with a statistics background should also get value out of this book. This is the book I wish I knew about when I was a statistics student.
Charyoll
For all the basic statistical tests, this book makes for a great reference.
Many worked examples (by hand) so you can see how it's all done, followed by really excellent explanations on how to interpret the results.

However, a word of caution: as I stated above "basic statistical tests". Do not expect the same treatment for some of the more exotic tests like factor analysis or principal component analysis. It's just not there.
nadness
This is an amazing comprehensive (1736 pages) encyclopedia of statistics. It gives every variation on every test, with detailed examples and tables. It has plenty of equations for those who want to do calculations themselves. But it is does not derive any equations or prove any theorems. It explains concepts in words (with examples), not equations. This makes it quite understandable by scientists (as well as statisticians). It is extremely well written. Although it purports to be comprehensive, no book really can be. It makes no mention of nonlinear regression, or model comparisons. Its coverage of survival curves is a bit weak (compared to the rest of the book), as is its coverage of modern (computer intensive) statistical methods. If you analyze data, you should have access to this book as a reference. No other book is so comprehensive and yet readable. Its price, per page, makes it an amazing bargain.
Coiriel
I am writing this after (trying) to use this book in my consulting practice. I purchased this book because I wanted a "one stop shop" for major statistical tests. This book somewhat accomplishes that, but in a way that has not been helpful most of the time. For example, it goes on ad-nauseum about the Z and t tests, yet the discussion about boostrapping and, to a greater extent, the multivariate techniques, is insufficient to really understand what is going on. Also, the chapters are very busy, so that its hard to get to "what do I calculate" in some instances.

I gave it two stars because, in terms of its breadth of topics, this book is indeed a compendium of the most commonly used procedures. However, partly due to the author's/publisher's desire for comprehensiveness, the usability of this book is almost zero! Advanced topics and useful information like boostrapping are lodged in "endnotes" that can go on for longer than the actual chapter, which gives the impression that the publishers/author didn't want to alter the structure of the book, but wanted to "jam in" more topics, so they just tacked them onto the most appropriate "test", even though these are more like "techniques" than full on tests.

Another feature that some may like is the copious referencing, which may be helpful for justifying the use of a particular test. However, I find that the rapid pace of statistical research means you can't rely on a smattering of papers to make your case. You really just need to dig into your actual dataset to find out what works.

Finally, I am a fan of non-parametric techniques, but I found only the most basic of them included here, whereas the book "Nonparametric Stastical Procedures" by Hollander, Wolfe and Chicken has a lot of really useful tests that are left out here.

In conclusion, I found myself turning to other books (read: more specialized or more basic) or to trusted internet sources when I needed to find a method. Trying to go from a research problem to a test using this book is next to impossible, as you will need to slog though its somewhat tedious layout.

The only really useful tool (for me) in this book is the "Test Chart" in the introduction: if you just copied these pages and then did google searches based on what it recommended, you'd come up with everything this book tells you, but for free, and with the possibility of finding other types of tests.

Bottom line: If you know what test you want to do, then you can find the procedure for free (internet). If you don't know what you're doing, then this book won't teach you (too terse and verbose...at the same time!). If you want a nice looking paperweight that makes you feel better, then perhaps you can get it. But it offers very little new material that cannot be found, more easily and coherently, from more basic or internet-based sources. As such, its unclear who would benefit from this book.
Mitars Riders
This book is an excellent comprehensive source reference for researchers, biostatisticians and risk assessor responsible for conducting statistical analysis. It can assist with statistical design selections as it provides numerous examples and explanations regarding the statistical results from the selected method.
Flocton
I found this book to be difficult to understand and written towards the statistician rather than the lay person. The pages are very thin and delicate, which is rather odd for a hardcover textbook.
Overall I was not satisfied and I returned it.
Binar
IT is hard for words to express exactly how much I hate this book!! IT is being used for my statistics class and it makes things so much more confusing than they need to be. it does not explain anything in terms that are easy to understand and would probably be best for a mad scientist type. The pages are thin and the print is for boring- it reminds me of a dictionary. The book is so dull and unengaging that i am stressed out after reading.... also there are no sample problems, or diagrams to explain things. i would definitely look for a better option. i would say the only good thing about this book is that it goes really in depth but im sure that can be found in other stats books.
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