Description

This course gives a brief introduction about how to use R language as a scientific programming language. R is developed from S plus, and is becoming very popular in statistics. This course covers an introduction about R, enviroment variables, descriptive statistics, graphics, regression etc.

Course Outline

The course aims at teaching students to learn not only the language itself but the way to program. So the student should be able to know how to achieve a specified goal in programing independently, which includes designing the algorithms, searching for commands, and debugging. Importantly, they also need to have the knowledge about the basic methodology in programing and statistics, so that they can interpret their output properly.

The outline of the course

1. Introduction
2. Variables, Vectors and Matrics
3. Data frames
4. Reading & Writing Data
5. Exploratory Data Analysis
6. Graphics
7. Programming

Teaching philosophy

1. R Search Page and run Examples at first (instead of read the long help at first, feel directly! efficient!)
2. Google
3. Google Code Search
4. When you do not know meanings of some codes, run it at first, modify some parameters & see changes in output.

Tips

1. Enough Comments/Standard Formats! Projects will be transferred from/to others; Consistency; smooth transfer between employee.
2. No Loops except really necessary . Use Matrix & Kronecker Product!
3. Plots: everything LARGE, visible after printing in A4; dark color (visible under sunshine); distinguishable by both line style/colors (print in Black/White)
4. All plots in PDF (transparent background), cut margins completely
5. Start from modifying the examples in course instead of writing new ones.

Literature

• An Introduction to R
• R Data Import/Export
• The R Reference Index
• Data Analysis and Graphics Using R
• Programmieren mit R