# What are the basics of data analysis

## Basics of data analysis with R

This book provides one application-oriented introduction into data evaluation with the free statistics environment R. It deals with descriptive evaluations just as comprehensively as inferential statistical analyzes. In addition to classic univariate methods, the book takes into account nonparametric tests, resampling methods and multivariate statistics. It also covers the various options for preparing data and creating diagrams. The statistical procedures are explained using examples and illustrated in many places with diagrams.

The book is aimed at everyone who wants to get to know R and use it in specific tasks without having previous experience with command-controlled programs or programming languages.

The book has been completely updated for the fifth edition: It now refers to version 4.0.0 of R, and the selection and display of additional packages used has also been adapted to the dynamic development. In addition, the section on data preparation in particular has been revised: In order to focus more on data science applications, it now presents the dplyr package in detail, contains an expanded representation of R-Markdown documents and discusses information on the reproducibility of evaluations.

PD Dr. Daniel Wollschläger For many years he taught at the Institute for Psychology at the Christian-Albrechts-Universität zu Kiel and is now at the Institute for Medical Biometry, Epidemiology and Computer Science at the University Medical Center of the Johannes Gutenberg University in Mainz.

First steps
Basic data entry and processing
Records
Manage commands and data
Tools for inferential statistics
Correlation and regression analysis
Parametric tests for dispersion and position parameters of distributions
Classic nonparametric methods
Resampling process
Multivariate method
Create diagrams
R as a programming language
Bibliography.

Publication date 13.11.2020 Statistics and its applications 50 b / w photos, 49 color photos Berlin German 168 x 240 mm 1314 g Mathematics / Computer Science►Mathematics►Computer Programs / Computer Algebra Mathematics / Computer Science►Mathematics► Probability / Combinatorics Data analysis • Data evaluation • Creating diagrams • Cross validation • Logistic regression • Nonparametric tests • Nonparametric tests • R • Resampling methods • Statistics • Statistics programs • Univariate methods 3-662-61735-8 / 3662617358 978-3-662-61735-9 / 9783662617359 New item