Quick links

• Introductory lecture slides
• VLE site
• Timetable on TimeEdit

 

This page includes information about aim and learning outcomes, teachers, literature, examination, examination procedures and course evaluation. The program for all teaching sessions can be found on a separate Course PM page.

 

Aim and learning outcomes

The course MVE495, Mathematical Statistics, gives an introduction to probability and statistical theory as well as to modern computational statistical methods provided by Python programming language. The aim of the course is to give students basic techniques to analyse and present data and account for their variability. It assumes a general mathematical knowledge; no other prerequisites are assumed.

The teaching of the course is based on the Virtual Learning Environment system (VLE).

Mathematical Sciences department's Stats VLE is a web-based system providing students with all the necessary tools to learn basic Probability and Statistics and practice problem solving on your own. It contains a variety of computer-generated questions covering the course curriculum as well as all the necessary supporting materials: statistical tables, hints, demos, etc. One may re-run the question-solution cycle as many times as felt necessary to deepen understanding of Statistics and to practice the techniques. It is complemented by the Study Guide with all the necessary theory which is directly accessible from within the VLE. Please, read the document VLE data import to Python  of the VLE's Help which will help you to work smoothly. You may use Python and coding environment like Visual Studio Code installed on your or lab computers, but you may also run Python directly from the VLE website.

Registration for the VLE  will open on Monday, 1/09. Here are instructions on how to get started. The student's work on the VLE is supported by assisted computer labs and drop-in consultation sessions on campus where all questions on the content of the course could be asked and help sought. For deeper understanding of the theory and further topics, The Statistics Study Guide is integrated into VLE and recordings of the lectures from 2021 are also provided.

Organisation of the study

The introductory lecture is on Monday 1st of September at 15:15-17:00 in SB-H1 auditorium. Handouts of the introductory lecture are available from VLE and above.

The main emphasis of the study is on your personal timely work within the VLE. The labs are not compulsory to attend; they are rather contact hours with the staff where you may and should ask questions on the course. Emailing questions on the study to staff is discouraged unless it is an administrative question or, if you think, you have found an error in the VLE.

Changes compared to the last occasion

The course switches from MATLAB to Python. Handwritten notes are no longer accepted at the exam. The past experience showed that some students were copying ChatGPT codes into their notes without proper understanding. The Statistics Study Guide linked with the VLE contains everything needed to answer VLE exam questions and will be available at the exam.

The students will be offered a choice to take the exam in the Inspera exam environment using their own laptops: a limited number of places will be available. The content will be the same as for the student opting to sit the exam at the university lab computers. The students who will be taking the exam in Inspera must use the Python environment provided by the VLE.

Teachers

Examiner: Sergei Zuyev

Lecturer: Sergei Zuyev

Teaching assistants and Lab supervisors: 

• Filip Björnåsen filip.bjornasen@gmail.com
• Louis Dao louis.dao.6801@gmail.com
• Elias Nyholm eliasny@chalmers.se
• Emil Nyström emilnyst@chalmers.se

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Course literature:

1. Statistics Study Guide, Available from within the VLE.

Also recommended:

1. Kerstin Vännman and Adam Jonsson. Matematisk statistik, Studentlitteratur, 2020. ISBN 978-93-44-13324-9. Available as a Hard copy (Links to an external site.) and a Digital copy
2.  Ulla Dahlbom. Matematisk statistik. HB Matematiklitteratur i Göteborg, 2003.
   ISBN 91-974428-0-1
3. Engelsk-svensk matematisk ordlista.

Recommended reading for Python:

1. 1. Free Python Tutorial For Beginners
   2. Python tutorial

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Use of AI tools

You are free to use any help for your studies, including AI tools, but note that you will need to show your knowledge at the exam from scratch: only access to the VLE page will be allowed (including the Study Guide and Statistical Tables)

Examination

The course has a total of 3 LADOK credits. The grade for the course is based on the results of the final examination on Thursday, 25th of September 2025. To pass the course, the examination mark should be at least 40%.

The student's grade for the course is U, 3,4, or 5 if the mark is, respectively, 39% or less, 40-59%, 60-79%, or 80% or more.

The resit examination will be held at the end of October, the second resit is planned for January 2026: the dates will be announced here in due time..

You do not need to book centrally for the exam: the booking opens in VLE in the mid-September.

Come to the booked auditorium 15 minutes before the start to install comfortably. The details will be communicated at the lecture and VLE in due time.

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Examination procedures

The exam consists of a random selection of questions,  the same type as in the VLE studies. You do not need to register centrally for the exam, but to book yourself via VLE. It will be held in a special exam computer environment. Python and the Study Guide will be available during the exam, but access to external disks, flash media, and all sites other than VLE will be blocked. So you would need to show your knowledge and computing skills from scratch.

At the exam, you should be able to demonstrate a valid ID. If you are entitled to an extended time, email me at sergei.zuyev@chalmers.se

Three days after the exam,  you can see your results in VLE.

 Any appeals concerning the obtained result must be submitted by email to the examiner.

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Course evaluation

At the beginning of the course, at least two student representatives should have been appointed to carry out the course evaluation together with the teachers. The evaluation takes place through conversations between teachers and student representatives during the course and at a meeting after the end of the course, when the survey result is discussed and a report is written. 

Guidelines for Course evaluation (Links to an external site.) in the Chalmers student portal.

Student representatives

The Minutes of the Staff - Student representatives meeting

Will appear here.

Program

The program can be found on the Course PM page.

 

 

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