Experimental design and data analysis for biologists /
"Requiring only introductory statistics and basic mathematics, this textbook avoids jargon and provides worked examples, data sets and R code, and review exercises. Designed for advanced undergraduates and postgraduates studying biostatistics and experiment design in biology-related fields, it...
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Main Authors: | |
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Group Author: | |
Published: |
Cambridge University Press,
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Publisher Address: | Cambridge, United Kingdom : |
Publication Dates: | 2024. |
Literature type: | Book |
Language: | English |
Edition: | Second edition. |
Subjects: | |
Summary: |
"Requiring only introductory statistics and basic mathematics, this textbook avoids jargon and provides worked examples, data sets and R code, and review exercises. Designed for advanced undergraduates and postgraduates studying biostatistics and experiment design in biology-related fields, it applies statistical concepts to biological scenarios"-- |
Item Description: | Revised edition of: Experimental design and data analysis for biologists / Gerry P. Quinn, Michael J. Keough. 2002. |
Carrier Form: | xix, 387 pages : illustrations ; 26 cm |
Bibliography: | Includes bibliographical references and index. |
ISBN: |
9781107036710 1107036712 9781107687677 1107687675 |
Index Number: | QH323 |
CLC: | Q-332 |
Call Number: | Q-332/Q74/2nd ed. |
Contents: | Introduction -- Things to know before proceeding -- Sampling and experimental design -- Introduction to linear models -- Exploratory data analysis -- Simple linear models with one predictor -- Linear models for crossed (factorial) designs -- Multiple regression models -- Predictor importance and model selection in multiple regression models -- Random factors in factorial and nested designs -- Split-plot (split-unit) designs: Partly nested models -- Repeated measures designs -- Generalized linear models for categorical responses -- Introduction to multivariate analyses -- Multivariate analyses based on Eigenanalyses -- Multivariate analyses based on (dis)similarities or distances -- Telling stories with data. |