Data Analysis and Visualization in R
Preface
Acknowledgments
Prerequisites
Datasets
Feedback
Introduction
I Get
1 R basics
2 Data wrangling
3 Tidy data and combining tables
II Look
4 Low dimensional visualizations
5 High dimensional visualizations
6 Graphically supported hypotheses
III Conclude
7 Resampling-based Statistical Assessment
8 Analytical Statistical Assessment
9 Statistical Assessments for Big Data
10 Linear Regression
11 Logistic Regression
12 Supervised Learning
Appendix
A Importing data
B R programming
C Additonal plotting tools
D Probabilities
Julien Gagneur, TUM
Published with bookdown

Data Analysis and Visualization in R (IN2339)

Datasets

Datasets used in this script are available to download as a compressed file here.