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Experimental design and data analysis for biologists / Gerry P. Quinn, Deakin University, Victoria, Michael J. Keough, University of Melbourne.

By: Contributor(s): Publisher: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2024Edition: Second editionDescription: xix, 387 pages : illustrations ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781107687677
Subject(s): DDC classification:
  • 23/eng/20230418 570.151 Q44 2024
LOC classification:
  • QH323.5 .Q85 2024
Contents:
Contents: List of Acronyms; Preface; 1. Introduction; 2. Things to Know Before Proceeding; 3. Sampling and Experimental Design; 4. Introduction to Linear Models; 5. Exploratory Data Analysis; 6. Simple Linear Models with One Predictor; 7. Linear Models for Crossed (Factorial) Designs; 8. Multiple Regression Models; 9. Predictor Importance and Model Selection in Multiple Regression Models; 10. Random Factors in Factorial and Nested Designs; 11. Split-plot (Split-unit) Designs: Partly Nested Models; 12. Repeated Measures Designs; 13. Generalized Linear Models for Categorical Responses; 14. Introduction to Multivariate Analyses; 15. Multivariate Analyses Based on Eigenanalyses; 16. Multivariate Analyses Based on (dis)similarities or Distances; 17. Telling Stories with Data; References; Glossary; Index.
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"-- Provided by publisher.
Holdings
Item type Current library Collection Call number Status Barcode
Books Books College Library General Circulation Section GC GC 570.151 Q44 2024 (Browse shelf(Opens below)) Available HNU005537

Revised edition of: Experimental design and data analysis for biologists / Gerry P. Quinn, Michael J. Keough. 2002.

Includes bibliographical references and index.

Contents: List of Acronyms; Preface; 1. Introduction; 2. Things to Know Before Proceeding; 3. Sampling and Experimental Design; 4. Introduction to Linear Models; 5. Exploratory Data Analysis; 6. Simple Linear Models with One Predictor; 7. Linear Models for Crossed (Factorial) Designs; 8. Multiple Regression Models; 9. Predictor Importance and Model Selection in Multiple Regression Models; 10. Random Factors in Factorial and Nested Designs; 11. Split-plot (Split-unit) Designs: Partly Nested Models; 12. Repeated Measures Designs; 13. Generalized Linear Models for Categorical Responses; 14. Introduction to Multivariate Analyses; 15. Multivariate Analyses Based on Eigenanalyses; 16. Multivariate Analyses Based on (dis)similarities or Distances; 17. Telling Stories with Data; References; Glossary; Index.

"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"-- Provided by publisher.

CAS Bachelor of Science in Biology

In English

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