图书简介

Part 1: The Conceptual Basis For Fitting Statistical Models; 1 General introduction; 2 Statistical modeling: a short historical background; 3 Estimating parameters: the main purpose of statistical inference; Part II: Applying The Generalized Linear Model to Varied Data Types; 4 The General Linear Model I: numerical explanatory variables; 5 The General Linear Model II: categorical explanatory variables; 6 The General Linear Model III: interactions between explanatory variables; 7 Model selection: one, two, and more models fitted to the data; 8 The Generalized Linear Model; 9 When the response variable is binary; 10 When the response variables are counts, often with many zeros; 11 Further issues involved in the modeling of counts; 12 Models for positive real-valued response variables: proportions and others; Part III: Incorporating Experimental and Survey Design Using Mixed Models; 13 Accounting for structure in mixed/hierachical structures; 14 Experimental design in the life sciences - the basics; 15 Mixed-hierachical models and experimental design data; Afterword; R packages used in the book; Appendix 1: Using R and RStudio: the basics (only available online at www.oup.com/companion/InchaustiSMWR); Appendix 2: Exploring and describing the evidence in graphics (only available online at www.oup.com/companion/InchaustiSMWR)

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