Experimental design and data analysis for biologists - Quinn, G. P. (Gerald Peter) 1956-; Keough, Michael J. (Cambridge, [England] Cambridge University Press, 2024)
"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.
Chapter 1 : Introduction -- Chapter 2 : Things to Know before Proceeding -- Chapter 3 : Sampling and Experimental Design -- Chapter 4 : Introduction to Linear Models -- Chapter 5 : Exploratory Data Analysis -- Chapter 6 : Simple Linear Models with One Predictor -- Chapter 7 : Linear Models for Crossed (Factorial) Designs -- Chapter 8 : Multiple Regression Models -- Chapter 9 : Predictor Importance and Model Selection in Multiple Regression Models -- Chapter 10 : Random Factors in Factorial and Nested Designs -- Chapter 11 : Split : Plot (Split : Unit) Designs -- Chapter 12 : Repeated Measures Designs -- Chapter 13 : Generalized Linear Models for Categorical Responses -- Chapter 14 : Introduction to Multivariate Analyses -- Chapter 15 : Multivariate Analyses Based on Eigenanalyses -- Chapter 16 : Multivariate Analyses Based on (Dis)similarities or Distances -- Chapter 17 : Telling Stories with Data.
Revised edition of: Experimental design and data analysis for biologists / Gerry P. Quinn, Michael J. Keough. 2002.
Includes bibliographical references and index.
Keywords: Biometry