Introduction to R for Terrestrial Ecology [electronic resource] : Basics of Numerical Analysis, Mapping, Statistical Tests and Advanced Application of R /

By:

Lakicevic, Milena [author.]

Contributor(s):

Material type: Text

TextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020Description: XVII, 158 p. 57 illus., 49 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783030276034

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

005.45 23

LOC classification:

QA76.76.C65

Online resources:

Click here to access online

Contents:

1. Types of Data in R -- 2. Numerical Analysis -- 3. Creating Maps -- 4. Basic Statistical Tests -- 5. Predictive Modeling with Machine Learning Applications -- Appendix.

In: Springer Nature eBookSummary: This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced applications of the R programming language. The main objective of the textbook is to serve as a guide for undergraduate students, who have no previous experience with R, but part of the textbook is dedicated to advanced R applications, and will also be useful for Masters and PhD students, and professionals. The textbook deals with solving specific programming tasks in R, and tasks are organized in terms of gradually increasing R proficiency, with examples getting more challenging as the chapters progress. The main competencies students will acquire from this textbook are: manipulating and processing data tables performing statistical tests creating maps in R This textbook will be useful in undergraduate and graduate courses in Advanced LandscapeEcology, Analysis of Ecological and Environmental Data, Ecological Modeling, Analytical Methods for Ecologists, Statistical Inference for Applied Research, Elements of Statistical Methods, Computational Ecology, Landscape Metrics and Spatial Statistics. .

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1. Types of Data in R -- 2. Numerical Analysis -- 3. Creating Maps -- 4. Basic Statistical Tests -- 5. Predictive Modeling with Machine Learning Applications -- Appendix.

This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced applications of the R programming language. The main objective of the textbook is to serve as a guide for undergraduate students, who have no previous experience with R, but part of the textbook is dedicated to advanced R applications, and will also be useful for Masters and PhD students, and professionals. The textbook deals with solving specific programming tasks in R, and tasks are organized in terms of gradually increasing R proficiency, with examples getting more challenging as the chapters progress. The main competencies students will acquire from this textbook are: manipulating and processing data tables performing statistical tests creating maps in R This textbook will be useful in undergraduate and graduate courses in Advanced LandscapeEcology, Analysis of Ecological and Environmental Data, Ecological Modeling, Analytical Methods for Ecologists, Statistical Inference for Applied Research, Elements of Statistical Methods, Computational Ecology, Landscape Metrics and Spatial Statistics. .

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