This course is an introduction to statistical analysis and statistical inference. Course topics include estimation, simple parametric and nonparametric tests, statistical dependence and correlation, linear regression analysis and analysis of variance. Software R is used in the exercises of this course.
Lecturer: Pauliina Ilmonen, pauliina.ilmonen(a)aalto.fi
Lectures: Thursdays 12.15-14.00 Hall C. The first lecture is on Thu 5.1.!
Lectures are an important part of this course. Attendance is not compulsory, but highly recommended. If you are unable to attend the lectures, you are expected to ask for notes from the other students.
Exercises are another very important part of this course. Attendance is not compulsory, but again highly recommended. You do get points by attending the exercises and by doing your homework assignments.
There are several exercise groups. Please attend one of them.
If none of the exercise group times is suitable for you, but you would still like to get exercise points, you may contact the course head assistant (matias.heikkila(a)aalto.fi). Note that you need a super good reason for getting points without attendance!
Students should be present and ready with their computers turned on at the beginning of the exercise session. Arriving late is not allowed. The first problem of each week's exercise session is a homework assignment. The homework assignment should be solved at home before the start of the session, using only pen, paper, and if necessary, a pocket calculator (no computers). Active participation is required at the exercise sessions. Students can obtain points from homework assignments and participation as follows: Active attendance plus homework assignment --> 0.5 points. Active attendance only --> 0.25 p. (As total one can obtain max 12*0.5=6 p.) Note that one can not get homework points without attending the corresponding exercise session! Note also that one can get homework assignment points even if the answer is not correct/complete. Trying your very best is enough! The exercise points are valid until the end of 2017.
How to pass this course?
You are expected to
Attend the lectures and be active - not compulsory, no points, but highly recommended. The first lecture is on Thursday 5.1.
Participate to exercises and solve your homework problems - not compulsory, but highly recommended - max 6 points.
Take the exam - max 24 points.
Max total points = 24 + 6 = 30: You need at least 15 points (or 12 points from the exam) in order to pass the course.
How to get a good grade?
Attend the lectures and be active!
Work hard on your homework assignments.
Be active in the exercises!
Study for the exam!
Grading is based on the total points as follows: at least 15p (or 12p from the exam) -> 1, at least 16p -> 2, at least 19p -> 3, at least 22p -> 4, at least 25p -> 5. Please note that you can not get grade 5 without attending the exercises. The reason for this is that learning to use R, and learning to conduct statistical analysis in practice, are crucial parts of the course.
In the exam, the focus is on the lecture material and on the lecture discussions.
In the exam you may have your pens and pencils, a ruler and an eraser. On top of that you may have one A4 of notes. The rules for the note are: size A4, text on one side only, it must be hand-written, your name has to be on the top right corner of the note. Please take an id-card with you to the exam. The exam organizers do not know you.
The first exam is on 05.04.2017 from 13.00 to 16.00. If you miss that, fail, or are not happy with your grade, then you can attend the second exam on 23.05.2017 from 09.00 to 12.00.