The course is divided in to three main components.
- A – Introduction to the statistics in R and R-studio. The basic functions in R, how to import and manipulate data. Visual presentation of data.
- B – Review of basic statistical concepts, hypothesis testing, different types of variables. Statistical tests for continuous and discrete variables. Using R for statistical analysis and tests for the validity of assumptions of the tests.
- C – Practical application of statistics in graduate student projects. Each students plans statistical analysis in his/her project, identifies suitable statistical tests and present to the group for discussion. methods.
Upon completing the course, the students should
- know how to use R either in R studio or directly through script fields
- be able to summarise and display data visually
- be familiar with common statistical tests for discrete and continuous variables
- understand the assumptions for the above statistical tests and know how to test for them
- be able to independently analyse data from their graduate work.