A popular entry-level guide into the use of R as a statistical programming and data management language for students, post-docs, and seasoned researchers now in a new revised edition, incorporating the updates in the R environment, and also adding guidance on the use of more complex statistical analyses and tools.
A popular entry-level guide into the use of R as a statistical programming and data management language for students, post-docs, and seasoned researchers now in a new revised edition, incorporating the updates in the R environment, and also adding guidance on the use of more complex statistical analyses and tools.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Andrew leads a research team studying community and evolutionary ecology. He has been using R and teaching quantitative methods for over 16 years. Owen leads a research team studying ecological forecasting. He has been using R and teaching quantitative methods for over 16 years. Dylan leads a research team studying population biology. He has been using R and teaching quantitative methods for over 15 years.
Inhaltsangabe
Preface 1: Getting and getting acquainted with R 2: Getting your data into R 3: Data management, manipulation, and exploration with dplyr 4: Visualising your data 5: Introducing statistics in R 6: Advancing your statistics in R 7: Getting started with generalised linear models 8: Pimping your plots: scales and themes in ggplot2 9: Closing remarks Appendices
Preface 1: Getting and getting acquainted with R 2: Getting your data into R 3: Data management, manipulation, and exploration with dplyr 4: Visualising your data 5: Introducing statistics in R 6: Advancing your statistics in R 7: Getting started with generalised linear models 8: Pimping your plots: scales and themes in ggplot2 9: Closing remarks Appendices
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