- 310 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Statistics for Linguists: An Introduction Using R
About this book
Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details. It contains many applied examples using the R statistical programming environment. Written in an accessible tone and style, this text is the ideal main resource for graduate and advanced undergraduate students of Linguistics statistics courses as well as those in other fields, including Psychology, Cognitive Science, and Data Science.
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Yes, you can access Statistics for Linguists: An Introduction Using R by Bodo Winter in PDF and/or ePUB format, as well as other popular books in Pedagogía & Enseñanza de artes y humanidades. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Title
- Copyright
- Contents
- Acknowledgments
- 0. Preface: Approach and How to Use This Book
- 1 Introduction to R
- 2 The Tidyverse and Reproducible R Workflows
- 3 Descriptive Statistics, Models, and Distributions
- 4 Introduction to the Linear Model: Simple Linear Regression
- 5 Correlation, Linear, and Nonlinear Transformations
- 6 Multiple Regression
- 7 Categorical Predictors
- 8 Interactions and Nonlinear Effects
- 9 Inferential Statistics 1: Significance Testing
- 10 Inferential Statistics 2: Issues in Significance Testing
- 11 Inferential Statistics 3: Significance Testing in a Regression Context
- 12 Generalized Linear Models 1: Logistic Regression
- 13 Generalized Linear Models 2: Poisson Regression
- 14 Mixed Models 1: Conceptual Introduction
- 15 Mixed Models 2: Extended Example, Significance Testing, Convergence Issues
- 16 Outlook and Strategies for Model Building
- References
- Appendix A. Correspondences Between Significance Tests and Linear Models
- Appendix B. Reading Recommendations
- Index
- Index of R Functions