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Cover: 9783030550196 | Environmental Data Analysis | An Introduction with Examples in R | xix
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Environmental Data Analysis
An Introduction with Examples in R
Buch von Carsten Dormann
Sprache: Englisch

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Beschreibung
Environmental Data Analysis is an introductory statistics textbook for environmental science. It covers descriptive, inferential and predictive statistics, centred on the Generalized Linear Model. The key idea behind this book is to approach statistical analyses from the perspective of maximum likelihood, essentially treating most analyses as (multiple) regression problems. The reader will be introduced to statistical distributions early on, and will learn to deploy models suitable for the data at hand, which in environmental science are often not normally distributed. To make the initially steep learning curve more manageable, each statistical chapter is followed by a walk-through in a corresponding R-based how-to chapter, which reviews the theory and applies it to environmental data. In this way, a coherent and expandable foundation in parametric statistics is laid, which can be expanded in advanced [...] content has been ¿field-tested¿ in several years of courses on statistics for Environmental Science, Geography and Forestry taught at the University of Freiburg.
Environmental Data Analysis is an introductory statistics textbook for environmental science. It covers descriptive, inferential and predictive statistics, centred on the Generalized Linear Model. The key idea behind this book is to approach statistical analyses from the perspective of maximum likelihood, essentially treating most analyses as (multiple) regression problems. The reader will be introduced to statistical distributions early on, and will learn to deploy models suitable for the data at hand, which in environmental science are often not normally distributed. To make the initially steep learning curve more manageable, each statistical chapter is followed by a walk-through in a corresponding R-based how-to chapter, which reviews the theory and applies it to environmental data. In this way, a coherent and expandable foundation in parametric statistics is laid, which can be expanded in advanced [...] content has been ¿field-tested¿ in several years of courses on statistics for Environmental Science, Geography and Forestry taught at the University of Freiburg.
Über den Autor

Carsten Dormann is a Professor of Biometry and Environmental System Analysis at the Faculty of Environment and Natural Resources, University of Freiburg, Germany. After completing his PhD in Plant Ecology at the University of Aberdeen, UK, he went on to become a statistical ecologist, with a research remit spanning from conservation ecology to the development of statistical methods, and from field experiments to population modelling. He currently teaches statistics at the BSc and MSc levels, from introductory classes to Bayesian statistics and machine learning.

Inhaltsverzeichnis
Preface.- The technical side: selecting a statistical software.- 1 Sample statistics.- 2 Sample statistics in R.- 3 Distributions, parameters and estimators.- 4 Distributions, parameters and estimators in R.- 5 Correlation and association.- 6 Correlation and association in R.- 7 Regression - Part I.- 8 Regression in R - Part I.- 9 Regression - Part II.- 10 Regression in R - Part II.- 11 The linear model: t-test and ANOVA.- 12 The linear model: t-test and ANOVA in R.- 13 Hypotheses and tests.- 14 Experimental Design.- 15 Multiple Regression.- 16 Multiple Regression in R.- 17 Outlook.- Index.
Details
Erscheinungsjahr: 2020
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: xix
264 S.
109 s/w Illustr.
27 farbige Illustr.
264 p. 136 illus.
27 illus. in color. With online files/update.
ISBN-13: 9783030550196
ISBN-10: 3030550192
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Dormann, Carsten
Auflage: 1st ed. 2020
Hersteller: Springer International Publishing
Springer International Publishing AG
Maße: 285 x 215 x 21 mm
Von/Mit: Carsten Dormann
Erscheinungsdatum: 21.12.2020
Gewicht: 0,952 kg
Artikel-ID: 118554042
Über den Autor

Carsten Dormann is a Professor of Biometry and Environmental System Analysis at the Faculty of Environment and Natural Resources, University of Freiburg, Germany. After completing his PhD in Plant Ecology at the University of Aberdeen, UK, he went on to become a statistical ecologist, with a research remit spanning from conservation ecology to the development of statistical methods, and from field experiments to population modelling. He currently teaches statistics at the BSc and MSc levels, from introductory classes to Bayesian statistics and machine learning.

Inhaltsverzeichnis
Preface.- The technical side: selecting a statistical software.- 1 Sample statistics.- 2 Sample statistics in R.- 3 Distributions, parameters and estimators.- 4 Distributions, parameters and estimators in R.- 5 Correlation and association.- 6 Correlation and association in R.- 7 Regression - Part I.- 8 Regression in R - Part I.- 9 Regression - Part II.- 10 Regression in R - Part II.- 11 The linear model: t-test and ANOVA.- 12 The linear model: t-test and ANOVA in R.- 13 Hypotheses and tests.- 14 Experimental Design.- 15 Multiple Regression.- 16 Multiple Regression in R.- 17 Outlook.- Index.
Details
Erscheinungsjahr: 2020
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: xix
264 S.
109 s/w Illustr.
27 farbige Illustr.
264 p. 136 illus.
27 illus. in color. With online files/update.
ISBN-13: 9783030550196
ISBN-10: 3030550192
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Dormann, Carsten
Auflage: 1st ed. 2020
Hersteller: Springer International Publishing
Springer International Publishing AG
Maße: 285 x 215 x 21 mm
Von/Mit: Carsten Dormann
Erscheinungsdatum: 21.12.2020
Gewicht: 0,952 kg
Artikel-ID: 118554042
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