MSC1620  Statistical Inference, Lecture, 9.1.202319.4.2023
This course space end date is set to 19.04.2023 Search Courses: MSC1620
Topic outline

1. Exercise groups and assistants. Assignment sheets for the exercises can be found at the bottom of this page.
Group Time Assistant Location Notes H01 Mon 16.15  18.00 Alisa Hakola Y344 H02 Tue 10.15  12.00 Timo Norrkniivilä Y344 H03 Tue 12.15  14.00 Alisa Hakola Y307a Updated for IVperiod H04 Tue 14.15  16.00 Timo Norrkniivilä U344 H05 Tue 16.15  18.00 Aleksi Avela Y344 H06 Wed 10.15  12.00 Kristian Jakobsson Y344 H07 Wed 12.15  14.00 Mikko Kaivola U6 On 25.1. in U9 H08 Thu 16.15  18.00 Mikko Kaivola Maari B (Linux)  182 H09 Fri 8.15  10.00 Jaakko Wallenius U351 H10 Fri 14.15  16.00 Jaakko Wallenius Y338 H11 Wed 16.15  18.00 Jaakko Wallenius Y344 H12 Wed 8.15  10.00 Kristian Jakobsson Y344 H13 Tue 10.15  12.00 Jaakko Wallenius Y338 2. Grading
The course grade (05) is determined based on the total of exam points (024) and exercise points (06),
 Total points = exam points + exercise points.
 15 total points <> grade 1
 16 total points <> grade 2
 19 total points <> grade 3
 22 total points <> grade 4
 25 total points <> grade 5
Additionally, grade 1 is also awarded to those who get 12 points from the exam alone.
Note, especially, that the highest grade (5) can not be obtained without any exercise points. The reason for this is that learning to use R, and learning to conduct statistical analysis in practice are essential learning goals of the course.
The exercise points are valid in all exams organized during the year 2023.If you miss some exercise session (e.g. the first week because of travels), please study the problems on your own. You can still continue the course.Exercises
There are several exercise groups in the course. Please attend one of them weekly and arrive in time in order to get exercise points from the homework.
The homework marks are checked at the beginning of each exercise session with attendance list which is filled at the beginning of each exercise session using MyCourses attendance box. One student is then randomly selected to present their work. The presentation can be R code, powerpoint show, whiteboard drawing, photograph of your handwritten solutions, latex, word, live drawing with paint  which ever you prefer as long as you are confident to give a short explanation of your work (we strongly encourage you to make and present your homework solution with / as R code). Please remember that your solution does not need to be correct  an attempt is enough  and that the assistant is there for you to complement and help to communicate your work if needed You can find the group times and locations in SISU.
The course exercises consist of two kinds of problems, homework problems and class problems.
 Homework problems: the first problem(s) of each week's exercise sheet is a homework problem which must be completed before that week's exercise session. Bring your solution to the homework problems with you to the exercise sessions (exception: first week's exercise). In the beginning of the exercise session, the course assistant will randomly ask some people who have solved the homework problem to present their solutions to everyone.
 Class problems: the remaining problems of each week's exercise sheet are class problems that will be solved together in the exercise sessions.
Additionally, some of the homework and class problems are optional. And although no points will be awarded from them, you are still heavily encouraged to go them through.
Exercise points will be awarded from the sessions as follows: 1/2 exercise points, if you actively attend the exercise session and had completed the week's homework problem.
 1/4 exercise points, if you actively attend the exercise session but had not completed the week's homework problem.
If you are unable to attend your own group, you are allowed to attend any of the other groups. If, on a given week, you cannot attend the exercises at all, contact the head assistant (Aleksi Avela) by email. Note that you need an extremely good reason for getting the points without attendance!
3. Assignment sheets
The planned assignment sheets can be found below.
The model solutions will be downloaded in the respective week's folder after the week's last exercise session.








It turns out that the R library "ElemStatLearn" containing the galaxy dataset has been removed from CRAN. Instead, you can download the data from here, or, alternatively, you can just inspect the summary and plot presented in the homework assignment, as it should already contain all the information required for answering the problem.
Please also note that the title of this exercise sheet incorrectly is "Exercise 10". You don't have to mind about this.

Package "ElemStatLearn" containing the galaxy dataset has been removed from CRAN. However, you can just inspect the plots presented in the homework assignment as they should already contain all the information required for answering the problem. Alternatively, you can download the data from here.
Please also note that the title of this exercise sheet incorrectly is "Exercise 11". You don't have to mind about this.

Please also note that the title of this exercise sheet incorrectly is "Exercise 12". You don't have to mind about this.
