Intro
Foreword
Preface
Contents
Chapter 1: Introduction
1.1 Introduction
1.2 What Is the Dataset About?
1.3 What You Will Learn
1.4 Why This Book?
1.5 How This Book Works
1.6 What Is "R" (and R-Studio)?
1.7 Who Is This Book For?
Chapter 2: How "R" Works
2.1 Downloading "R" and R-Studio
2.2 What R-Studio Looks Like
2.3 Running Simple Codes in the "R"-Console
2.4 To Practice with a More Advanced Code
2.5 Getting Help in "R"
2.6 The Hash Symbol #
2.7 The Problem of Missing Data
2.8 Misspelling the Code

2.9 Setting the Working Directory
2.10 Working with Scripts
2.11 R-Packages
2.12 Installing R-Packages
2.13 Loading R-Packages
2.14 How Many R-Packages Do We Need?
2.15 Conclusions
Further Readings
Chapter 3: Exploratory Data Analysis in "R"
3.1 Software and R-Package Required for This Chapter
3.2 Importing a Dataset into "R"
3.3 Fundamental Function to Explore a Dataset
3.4 Subsetting
3.5 Subsetting with Base-R
3.6 More Examples of Basic Subsetting
3.7 The Attach Function
3.8 Storing a Dataset as a Tibble for Use with the tidyverse R-Package

3.9 Frequently Used Subsetting Functions
3.10 Conclusions
Further Readings
Chapter 4: Data Types in "R"
4.1 Software and R-Packages Required for This Chapter
4.2 Where to Find the Example Dataset and the Script for This Chapter
4.3 What Is the Nature of Our Data?
4.4 Numeric Data
4.5 Integer
4.6 Character
4.7 Factors
4.8 Variable Classification
4.9 Misleading Data Encoding
4.10 Different Types of Variables Need Different Types of Statistical Analysis
4.11 Data Transformation and the Benefit of Continuous Variables
4.12 Missing Values

4.13 The CreateTableOne Function
4.14 Conclusion
Further Readings
Chapter 5: Data Distribution
5.1 Software and R-Packages Required for This Chapter
5.2 Where to Download the Example Dataset and the Script for This Chapter
5.3 Normality Testing
5.4 Histogram
5.5 Normality Testing
5.6 More About Visual Inspection with Regard to Normality
5.7 Do We Need to Test for Normality in All Cases?
5.8 Central Limit Theory
5.9 Properties of Normal Distribution
5.10 Subsetting for Normality Testing
5.11 Hint from the Grammar of Graphic
5.12 Boxplot

5.13 How to Treat Non-numeric Variables
5.14 Plotting Categorical Variables
5.15 Conclusion
Further Readings
Chapter 6: Precision, Accuracy and Indices of Central Tendency
6.1 Software and R-Packages Required for This Chapter
6.2 Where to Download the Example Dataset and the Script for This Chapter
6.3 Precision
6.4 The Relation Between Sample Size and Precision
6.5 Variance and Standard Deviation
6.6 Population and Sample Variance
6.7 Standard Error of the Mean vs Standard Deviation
6.8 Accuracy and Confidence Intervals
6.9 Mean, Median, Mode