R language course 2401-K-MF-JR
1. Basics
Data types and variables
Vectors
Functions
Operators part 1
Operators part 2
Frequently used functions
Statistical parameters
Lists
Control statements
Functions (continued)
Attributes
2. Multidimensional data types
Matrices and arrays
Matrix operations
Factors
Data frames
CSV files
Data processing example
R script
File handling
3. Basics of statistics
Graphical data analysis
Linear Regression
Ascombe's Quarter
Correlation
Hypothesis testing - theory
Hypothesis testing - example
4. Packages
Installing and loading packages
dplyr package - filtering, sorting and data processing
tidyr package - wide and long form of data
ggplot2 - Graphs
stringi package - string operations
5. Machine learning
caret package
Supervised learning - Classification
Unsupervised learning - Clustering
6. Creating packages
7. Test
8. Practising on real data
9. Final project or test
Prerequisites
Course coordinators
Bibliography
Jared P. Lander R for everyone. Advanced analysis and Graphics, Addison-Wesley Data & Analytics Series ---
Hadley Wickham, Garrett Grolemund R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, O'Relly 2016
Andy Field Discovering Statistics Using R, Sage Publications Ltd 2012
Brian S. Everitt, Torsten Hothorn A handbook of statistical analyses using R, z-lib.org (e-book)
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: