R/RStudio生物学のための統計学入門(第2版)<br>The New Statistics with R : An Introduction for Biologists (2ND)

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R/RStudio生物学のための統計学入門(第2版)
The New Statistics with R : An Introduction for Biologists (2ND)

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  • 製本 Hardcover:ハードカバー版/ページ数 278 p.
  • 言語 ENG
  • 商品コード 9780198798170
  • DDC分類 570.285

Full Description

Statistical methods are a key tool for all scientists working with data, but learning the basics continues to challenge successive generations of students. This accessible textbook provides an up-to-date introduction to the classical techniques and modern extensions of linear model analysis-one of the most useful approaches for investigating scientific data in the life and environmental sciences. While some of the foundational analyses (e.g. t tests, regression, ANOVA) are as useful now as ever, best practice moves on and there are many new general developments that offer great potential. The book emphasizes an estimation-based approach that takes account of recent criticisms of over-use of probability values and introduces the alternative approach that uses information criteria.

This new edition includes the latest advances in R and related software and has been thoroughly "road-tested" over the last decade to create a proven textbook that teaches linear and generalized linear model analysis to students of ecology, evolution, and environmental studies (including worked analyses of data sets relevant to all three disciplines). While R is used throughout, the focus remains firmly on statistical analysis.

The New Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners in the fields of ecology, evolution and environmental studies.

Contents

1: Introduction
2: Motivation
3: Description
4: Reproducible Research
5: Estimation
6: Linear Models
7: Regression
8: Prediction
9: Testing
10: Intervals
11: Analysis of Variance
12: Factorial Designs
13: Analysis of Covariance
14: Linear Model Complexities
15: Generalized Linear Models
16: GLMs for Count Data
17: Binomial GLMs
18: GLMs for Binary Data
19: Conclusions
20: A Very Short Introduction to R

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