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EXERCISES.md

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Bayesian Data Analysis course exercises

Exercises and evaluation criteria are in exercises folder. Exercises are submitted in peergrade.

(Please free to use these exercises in self study and other courses, but please do not publish complete answers online).

Exercise sessions

One can get personal help in in weekly exercise sessions. The sessions are voluntary and one may come and go as pleases during the sessions. Queuing system may be used if there will be too many students in some hours.

Weekly assignment details

There are 9 weekly exercises (assignments in peergrade). Students return their answers to peergrade by the end of the week (hand-in period). The exercises are introduced on Mondays. The deadlines are Sunday 23:59 (the dates are given in the table below). After this, each student grades 3 random other students' answers with detailed online form in peergrade during Monday to Wednesday (peer grading period). After peergrading, each student to should provide reactions to the feedback (e.g. not helpful/helpful). If a student receives inappropriate grading or reaction, they may "flag" it for TAs to check from Wednesday to Sunday (flagging period). Strongly conflicting gradings are also manually checked by TAs (after flagging period).

Assignments can be found from exercises folder

NOTE: The assignments instructions on github are still being updated and individual exercises are not guaranteed to be up to date until Monday (4am) of the hand-in period of the corresponding exercise week (See the deadlines below, e.g. first exercise is not guaranteed to be up to date until 9.9 at 8am).

Report all results in a single, anonymous *.pdf -file and submit it in peergrade. Include also any source code to the report (either in appendix or embedded in the answer). By anonymity it is meant that the report should not contain your name or student number. In addition to the correctness of the answers, the overall quality and clearness of the report is also evaluated.

The exercises are mostly solved using computer (R or Python). Related demos for each exercise are available in GitHub (links in Materials section). Exercise help sessions are organised on Wednesdays 14:15-16, Thursdays 12:15-14 and Fridays 10:15-12 (check the room of the day from Oodi). We will have an additional slot in the first week on Wednesday 11.9 from 12:15-14. The location may change from week to week, hence it is recommended to check the time and location every week from Oodi.

The sessions are very informal, a bit similar to service teaching (laskutupa) of the basic math courses. No need to register, feel free to come and ask TAs or join forces with some friends (each student must answer individually though). Participating to the exercise sessions is not required for passing the course. If one can solve all exercises without any help, it is totally OK to skip the exercise sessions. On the other hand, if some exercise feels hard, it is totally OK to attend all exercise sessions! It is also OK to attend the exercise sessions only for a while.

For those who are self studying or who miss several assignment hand-ins for a good reason, there is possibility to hand-in all assignments once in January.

Assignment scoring

Points are given from both submitting an assignment and giving feedback. Submission performance gives 70 % and feedback performance gives 30 % of the total score. Only the student's who returned assignment are allowed to give feedback to others.

In peergrade, the resulting grade is formed by comparing one's performance to the others. Thus, one should not worry about getting 100 % score. A critical reviewer will also affect other students' grading. In addition, a question can always be flagged for course personnel to check.

In addition to the peergrade score, one can get some bonus points from slack activity. Slack activity will not count for maximum assignment score. Other students' Slack activity will not affect one's resulting grade, i.e. there is no need to try to perform in the Slack or to take any part in it at all.

We have noticed in previous years that some students return an empty pdf to peergrade to still get points from giving feedback. This is not allowed. If a student returns an empty pdf or it is obvious from the pdf that the student hasn't done any effort for the assignment, the student is not allowed to give feedback. The course staff will monitor returned assignments, and negative points will be awarded to empty assignments. If any student is reviewing an empty pdf, please contact course staff.

Submission score

Within each assignment, there are two sections "Basic requirements" and "Overall quality of the report". Each of these always gives 7.5 % of that assignment's total score. The remaining 85 % is distributed evenly to the rest of the sections. Within each section, the points are distributed evenly among each question. In each question, the points are linearly scaled (yes/no: 1 / 0, three options: 1 / 0.5 / 0, four options: 1 / 0.666 / 0.333 / 0, etc).

Each question score is averaged from all the received feedback. If a flag is raised and course personnel grades the question, it will override all the received feedback scores.

There are 9 assignment rounds in total. The deadlines for the assignments are given below.

Feedback score

More info on the feedback score can be found here. Note that the feedback score system has been simplified from previous years.

Be polite

Remember to be polite when giving feedback and reacting to feedback. Do not spend long time to fight for grading of one question from one student. If you don't agree you can flag or in extreme case contact TAs, but do also remember than in most of the cases, which we've seen, the students have been fighting for points which have less than 1/1000 effect on the final score. Long fight for that is not worth it. If you get feedback which make you angry, breath and wait a moment before unleashing your anger back. We ask you to honor the system and be polite to your peers.

Project work details

Project work is done in groups of 1-3 persons. Preferred group size is 2. Groups of 1-2 persons are assumed to do same amount of work per group. Group of 3 persons is assumed to do 50% more work.

The groups will get help for the project work at the exercise help sessions. When there are no weekly assignments, the exercise sessions are still organized for helping in the project work.

Important dates for 2019 fall

Task Topic Published Deadline Points
Assignment 1 Background 9.9 (week 37) 15.9 at 23:59 3
Assignment 2 Chapters 1 and 2 16.9 (week 38) 22.9 at 23:59 3
Assignment 3 Chapters 2 and 3 23.9 (week 39) 29.9 at 23:59 9
Assignment 4 Chapters 3 and 10 30.9 (week 40) 6.10 at 23:59 6
Assignment 5 Chapters 10 and 11 7.10 (week 41) 13.10 at 23:59 6
Assignment 6 Chapters 10-12 and Stan 14.10 (week 42) 27.10 at 23:59 6
Evaluation week (21-28.10)
Project Projects introduced: form a group of 1-3 (2 is preferred) 28.10 (week 44) 3.11 at 23:59 -
Assignment 7 Chapter 5 28.10 (week 44) 3.11 at 23:59 6
Project Decide topic and start the project (no assign. on week 45) 10.11 at 23:59 -
Assignment 8 Chapter 7 11.11 (week 46) 17.11 at 23:59 6
Assignment 9 Chapter 9 18.11 (week 47) 24.11 at 23:59 3
Project Finish the project work (no assign. on weeks 48 & 49) 8.12 at 23:59 24
Project presentation Present project work during week 50 (evaluation week)