The course is about regression analysis using the software R. The theoretical goal is to learn what statistical methods to use and their limitations. The applied goal is to code the statistical methods with the software R. Many examples with real data are presented to illustrate the statistical methods and their use with the software R. The emphasize will be on financial data.
The course follows Linear Models with R (from Julian J. Faraway, Edition 1) book content. We aim to cover Ch. 1-4 of the book. Students will notice that in those chapters, matrix notation and calculation are often used. Although it is better to have some background on matrix notation and calculation, the student can get through with no prerequisite. It will be slightly harder for the student. However, the student will not be asked about matrix calculation or any other theoretical aspect of the course in the homework.
This course is not all about R, but some learning of this programming language is necessary to understand the book.
Students need to be confident with the language R, so that they can interpret the results obtained when following the book content.
Some students have no background at all in any programming language, and it will require more effort from them. The goal of this course is not that you become an expert of R, but rather that you know enough.
Before starting to work on Homework 1, you need to download R (without R, you cannot follow the book and do the homework). You can actually download R
here. Now that you have installed it, you can start to launch it, and you will see the R console.
Try to type 2+3, and then press "enter", and you should see 5 as a result. Students have to use the friendly interface user for R called Rstudio. RStudio is available
here. Once you have installed RStudio, you can launch it. From now on, you do not need to use the
R console, so you do not need to launch R application directly again (except for the part 1.2 of the tutorial on R that follows). Now it is time that you work
scrupulously going through Chapter 1 and Chapter 2 of this tutorial.
A very good complement that students should read is Appendix A (pp. 227-228) and Appendix B (pp. 229-232) in the textbook. Once you have completed the tutorial and read the appendices,
you can start reading the book from its introduction and Chapter 1 and do Homework 1.
The evaluation will be based on three homework (each will count for 1/3 of the final grade).
Homework should be PRINTED and NOT handwritten and handed to me in the lectures from the calendar. You have to use a typing language such as Word.
All the questions should be answered with English sentences (I will not grade any homework
which does not contain sentences as response to the questions). The included plot should be always described with a title.
Graded homework will be given back graded in the next class.