Experimental design and data analysis for biologists /
Quinn, G. P. 1956-
Experimental design and data analysis for biologists / Gerry P. Quinn, Deakin University, Victoria, Michael J. Keough, University of Melbourne. - Second edition. - xix, 387 pages : illustrations ; 26 cm
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"--
CAS Bachelor of Science in Biology
In English
9781107687677
2023005179
Biometry.
QH323.5 / .Q85 2024
570.151 Q44 / 2024
Experimental design and data analysis for biologists / Gerry P. Quinn, Deakin University, Victoria, Michael J. Keough, University of Melbourne. - Second edition. - xix, 387 pages : illustrations ; 26 cm
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"--
CAS Bachelor of Science in Biology
In English
9781107687677
2023005179
Biometry.
QH323.5 / .Q85 2024
570.151 Q44 / 2024
