Modern Statistics for the Life Sciences by Alan Grafen and Rosie Hails (2002, Trade Paperback)

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Modern Statistics for the Life Sciences by Alan Grafen, Rosie S. Hails. Author Alan Grafen, Rosie S. Hails. This textbook teaches statistics in a different way. The computer revolution has finally made it possible to teach life sciences undergraduates how to use the statistics they really need to know - this book provides thecourse materials needed to fulfil that possibility.

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Product Identifiers

PublisherOxford University Press, Incorporated
ISBN-100199252319
ISBN-139780199252312
eBay Product ID (ePID)2239423

Product Key Features

Number of Pages368 Pages
LanguageEnglish
Publication NameModern Statistics for the Life Sciences
Publication Year2002
SubjectProbability & Statistics / General, Life Sciences / General, General, Life Sciences / Biology
TypeTextbook
AuthorAlan Grafen, Rosie Hails
Subject AreaMathematics, Science
FormatTrade Paperback

Dimensions

Item Height0.8 in
Item Weight22.8 Oz
Item Length9.7 in
Item Width6.7 in

Additional Product Features

Intended AudienceCollege Audience
LCCN2002-283238
Dewey Edition21
Reviews'The book is well laid out and concepts are very well explained by making effective use of diagrams and geometric representations. There are many analyses of example data sets to ilustrate the application the methods and the interpretation of the output'. Biometrics 59, 200-209, March2003., "Grafen and Hails have written a very nice book...many examples also serveto highlight design or analysis errors that are commonly made and encourageconstructive critism: learning from mistakes is, I think, a very powerfulapproach." Animal Behaviour 2003, 'The book is well laid out and concepts are very well explained by making effective use of diagrams and geometric representations. There are many analyses of example data sets to ilustrate the application the methods and the interpretation of the output'. Biometrics 59, 200-209, March 2003."it is a stepping-stone between one's first statistics course and what one really needs as a professional biologist. That said, it is the best stepping-stone on the market". Trends in Ecology and Evolution, 2003."Grafen and Hails have written a very nice book...many examples also serve to highlight design or analysis errors that are commonly made and encourage constructive critism: learning from mistakes is, I think, a very powerful approach." Animal Behaviour 2003, "Grafen and Hails have written a very nice book...many examples also serve to highlight design or analysis errors that are commonly made and encourage constructive critism: learning from mistakes is, I think, a very powerful approach." Animal Behaviour 2003, "it is a stepping-stone between one's first statistics course and what one really needs as a professional biologist. That said, it is the best stepping-stone on the market". Trends in Ecology and Evolution, 2003.
IllustratedYes
Dewey Decimal570.7/24
Table Of ContentWhy use this book1. An introduction to the analysis of variance2. Regression3. Models, parameters and GLMs4. Using more than one explanatory variable5. Designing experiments - keeping it simple6. Combining continuous and categorical variables7. Interactions - getting more complex8. Checking the models A: Independence9. Checking the models B: The other three assumptions10. Model selection I: Principles of model choice and designed experiments11. Model selection II: Data sets with several explanatory variables12. Random effects13. Categorical data14. What lies beyond?Answers to exercisesRevision section: The basicsAppendix I: The meaning of p-values and confidence intervalsAppendix II: Analytical results about variances of sample meansAppendix III: Probability distributionsBibliographyWhy use this book1. An introduction to the analysis of variance2. Regression3. Models, parameters and GLMs4. Using more than one explanatory variable5. Designing experiments - keeping it simple6. Combining continuous and categorical variables7. Interactions - getting more complex8. Checking the models A: Independence9. Checking the models B: The other three assumptions10. Model selection I: Principles of model choice and designed experiments11. Model selection II: Data sets with several explanatory variables12. Random effects13. Categorical data14. What lies beyond?Answers to exercisesRevision section: The basicsAppendix I: The meaning of p-values and confidence intervalsAppendix II: Analytical results about variances of sample meansAppendix III: Probability distributionsBibliography
SynopsisThis textbook teaches statistics in a different way. It is aimed at undergraduate students in the life sciences, and it will also be invaluable for many graduate students. It makes the powerful methods of model formulae and the General Linear Model accessible to undergraduates for the first time. The computer revolution has finally made it possible to teach life sciences undergraduates how to use the statistics they really need to know - this book provides the course materials needed to fulfil that possibility. This text presents the fundamental statistical concepts without being tied to any one statistical package., This textbook teaches statistics in a different way. It is aimed at undergraduate students in the life sciences, and will also be invaluable for many graduate students. It makes the powerful methods of model formulae and the General Linear Model accessible to undergraduates for the first time. The computer revolution has finally made it possible to teach life sciences undergraduates how to use the statistics they really need to know - this book provides the course materials needed to fulfil that possibility., Model formulae represent a powerful methodology for describing, discussing, understanding, and performing the component of statistical tests known as linear statistics. It was developed for professional statisticians in the 1960s and has become increasingly available as the use of computers has grown and software has advanced. Modern Statistics for Life Scientists puts this methodology firmly within the grasp of undergraduates for the first time. The authors assume a basic knowledge of statistics--up to and including one and two sample t-tests and their non-parametric equivalents. They provide the conceptual framework needed to understand what the method does--but without mathematical proofs--and introduce the ideas in a simple and steady progression with worked examples and exercises at every stage. This innovative text offers students a single conceptual framework for a wide range of tests-including t-tests, oneway and multiway analysis of variance, linear and polynomial regressions, and analysis of covariance-that are usually introduced separately. More importantly, it gives students a language in which they can frame questions and communicate with the computers that perform the analyses. A companion website, www.oup.com/grafenhails, provides a wealth of worked exercises in the three statistical languages; Minitab, SAS, and SPSS. Appropriate for use in statistics courses at undergraduate and graduate levels, Modern Statistics for the Life Sciences is also a helpful resource for students in non-mathematics-based disciplines using statistics, such as geography, psychology, epidemiology, and ecology.
LC Classification NumberQA276.G7125 2002

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