Introduction to statistical data analysis with R

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( 18 )
228 pages
Idioma:
 English
The book contains an introduction to descriptive and inferential statistics applying the statistical software R. The analyses are introduced and discussed using real data.
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Sobre o autor

Matthias Kohl ist Professor für Mathematik in Biology und Medizin und leitet das Masterprogramm “Precision Medicine Diagnostics (M.Sc.)” an der Hochschule Furtwangen. Er ist Mitglied des Institute of Precision Medicine und des Baden-Württemberg Center of Applied Research (BW-CAR). Er hat mehr al

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The book offers an introduction to statistical data analysis applying the free statistical software R, probably the most powerful statistical software today. The analyses are performed and discussed using real data. After a brief description of the statistical software R, important parameters and diagrams of descriptive statistics are introduced. Subsequently, recommendations for generating diagrams are provided, where special attention is given to the selection of appropriate colors. The second half of the book addresses the basics of inferential statistics. First, a number of probability distributions are introduced and their applicability is illustrated by examples. Next, the book describes how the parameters of these distributions, which are unknown in practice, may be estimated from given data. The final chapter introduces statistical tests and reviews the most important tests for practical applications.

  1. Statistical Software R
    1. R and its development history
    2. Structure of R
    3. Installation of R
    4. Working with R
    5. Exercises
  2. Descriptive Statistics
    1. Basics
    2. Excursus: Data Import and Export with R
    3. Import of ICU-Dataset
    4. Categorical Variables
    5. Metric Variables
    6. Exercises
  3. Colors and Diagrams
    1. Colors
    2. Excursus: Export of Diagrams
    3. Diagrams
    4. Exercises
  4. Probability Distributions
    1. Discrete Distributions
    2. Continuous Distributions
    3. Exercises
  5. Estimation
    1. Introduction
    2. Point Estimation
    3. Condence Intervals
    4. Exercises
  6. Statistical Tests
    1. Introduction
    2. Examples
    3. Exercises
This book is safe as an airbag while I ride through the jungle of R. Its a great book.
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