Osion kuvaus

  • Yleinen

    Welcome to the course Statistical Inference 2023! These MyCourses pages will host the lecture plan, lecture slides, exercise assignments, and other material.

    PLEASE NOTE THAT THE REGISTRATION TIME IN SISU ENDS 8.1.2023 23.59!


    In the exercise sessions, we will be using R programming language and use R Studio Desktop as the graphical user interface for R.

    Note that Introduction to R programming will be lectured as an intensive course on 21.1.-22.1. in case you are interested. See here: https://mycourses.aalto.fi/course/view.php?id=38219#section-0

    You can also get assistance with the exercises in the Laskutupa (i.e., mathematics tutoring lab).

    Lecturer: Jukka Kohonen.

    Head assistant: Aleksi Avela. Contact the head assistant (or the assistant of your own group) in questions related to exercise sessions.

    When contacting the teachers by e-mail, start by mentioning the course code. (Otherwise how can the teacher know which of their courses you are talking about?)


  • Luennot

    The course lectures are on Thursdays at 8.15-10.00 in the hall U2.

    Exception: The last lecture L12, on 13.4., will actually be groupwork in Zoom (see the table below for links).

    The lectures will be video recorded, so you can watch them afterwards. Also available are recordings from spring 2022 Zoom lectures. Note that the lecture room videos have 2--3 video streams (camera + one or two screens). You can switch between them when watching from Panopto.

    On the live lectures, you are encouraged to ask questions. Sometimes the questions may warrant a longer answer than I can provide on the lecture, and I will post extended answers here under the Q&A thread. (The thread also contains questions and answers from the previous year.)

    In the column "Planned topic", you can find the slides for the planned lecture. Actual lectures may run faster or slower. If the actual lectures are lagging behind, you may want to read the slides on your own, for example, if you need tools for the exercises. Until updated, slides from previous year are available here.

    Lecture plan
    Lecture    Day
    		Planned topic, slides
    		     Videos etc.  
    		Lecture slides
    updated
    		 Example code
    L1
    		 12.1.
    		 Descriptive statistics
    		 new, old, Q&A 
    		11.1.
    		 L1 code
    L2 19.1.
    		 Confidence intervals and hypothesis testing  
    		(no new video,
    see old) old
    		19.1.
    		 L2 code
    L3 26.1.  
    		Non-parametric tests (distribution-free)
    		 new, old, Q&A
    		L3 code
    L4
    		 2.2.
    		 Inference for binary data
    		 new, old,
    extra slides
    		L4 code
    L5
    		 9.2.
    		 Distribution tests
    		 new, old
    		L5 code
    L6
    		 16.2.
    		 Correlation and dependence
    		 new, old
    		L6 code


    		Period break
    L7
    		 2.3.
    		 Linear regression I
    		 (no new video,
    see old), old
    		L7 code
    L8
    		 9.3.
    		 Linear regression II
    		 new (note two screens)
    old, Q&A
    		L8 code
    + matlab code showing regression plane
    L9
    		 16.3.
    		 Linear regression III,
    Model complexity and Cross validation
    lecture cancelled,
    read slides and watch old video
    		 old
    		L9 code
    L10
    		 23.3.
    		 ANOVA
    		 new, old
    		L10 code
    L11
    		 30.3.
    		 Kernel regression
    		 new, old
    		L11 code
    L12 13.4.
    		 Reflection groupwork:
    instructions, Zoom link, Miro board, L12 attendance
    		 Miro results
    as PDF file



  • Tehtävät

    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 IV-period 
     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 (0-5) is determined based on the total of exam points (0-24) and exercise points (0-6),

    • Total points = exam points + exercise points.
    The total points correspond to the following course grades,
    • 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 hand-written 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.
    Exception: during the first week's exercise, the full 1/2 points will be awarded solely based on active attendance. Note that active attendance to the exercise sessions is mandatory if you want to obtain any exercise points. 

    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 e-mail. 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.

  • Attendance

    Saatavilla vasta, kun: You are a(n) Opiskelija

    This page contains the attendance boxes which are used to mark your attendance and homework points in exercise sessions. Please mark your points to the group which you are currently attending even if you have joined into another group in SISU.

    • Mark "Present and Homework" if you attend to the exercise session and have done the week's homework
    • Mark "Present" if you attend to the exercise session but have not done the week's homework

    The homework marks are checked at the beginning of each exercise session and one student is randomly selected to present their work. The presentation can be R code, powerpoint show, whiteboard drawing, photograph of your hand-written 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. 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.