Adatfeldolgozás alapjai R-rel. Alkalmazások a környezettudományban
Data Processing with R. Applications in the Environmental Sciences

Author(s): Andrea Rebeka Zsigmond
Subject(s): Geography, Regional studies, Environmental Geography
Published by: Scientia Kiadó
Keywords: environmental science studies; R – a free software for statistical analyses and data processing; basics of statistics;
Summary/Abstract: This book is designed for students involved with environmental science studies. It is a useful guide for them to become acquainted with R, which is a free software for statistical analyses and data processing. Today, R is accepted and widely used in the scientific community. The main reason of its popularity is the boundless possibilities R gives for users through the packages developed by statisticians all over the world. The book contains eight chapters, at first providing information about the basics of statistics and experimental design in the environmental sciences. The following chapters present the language of R and the main commands for handling a data frame and constructing simple plots such as histograms, box plots, or scatter plots. Through chapters three to seven, the distributions of continuous and discrete data and the most relevant hypothesis testing procedures are detailed. This part is the core of the book, which provides an expansively treated knowledge for the reader to feel themselves confident in processing experimental data with R in a scientific manner. The eighth chapter is dedicated to regression analysis. This chapter presents the linear regression and the generalized linear models confined to one independent variable. The book relies on a comprehensive bibliography containing Hungarian, English, and Romanian scientific articles and books. For students who want to deepen their English statistical language, The R Book (Crawley, 2013) is highly recommended. There are also some books written in Romanian language that are also recommended: Analiza statistică folosind limbajul R (Păun Păun 2009) and Noţiuni de statistică aplicată cu exemple în R (Păun 2016). For learners, it is recommended to pass through the chapters chronologically because the knowledge the book gives is logically constructed. For those who are familiarized with the statistical tools, the book can be used as a handbook for finding a useful solution in R for the given problem.

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