MVE540 Matematisk statistik V26

  • Quick links

    VLE site

    Timetable

    Introductory lecture handouts

    Introduction

    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 Detailed program page.

    Aim and learning outcomes

    The course MVE540, Mathematical Statistics, gives an introduction to probability and statistical theory as well as to modern computational statistical methods provided by the Python software language. Make sure you have Python installed on your working computer alongside your preferred coding software. Freely available Visual Studio Code is recommended.  The course aims to give students basic techniques to analyse and present data and account for variability. It assumes a general mathematical knowledge; no other prerequisites are assumed.

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

    The 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 their 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. 

    The student's work on the VLE is supported by the theory survey lectures and assisted computer labs. How to get started with the VLE will be explained here in due time.

    Teachers

    Examiner: Sergei Zuyev

    Lecturer: Sergei Zuyev

    Teaching assistant and Lab supervisor: 

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    Course literature

    Also recommended:

    •  Kerstin Vännman and Adam Jonsson. Matematis statistik, Studentlitteratur, 2020.  ISBN 978-93-44-13324-9

    Recommended reading for Python:

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    Use of AI tools

    You may use any help and tools, including AI, while working on the course, but note that at the exam, you will not be able to access the internet or smartphone or mount a network or portable drives. You must show from scratch how you mastered the course content.

    Changes compared to the last occasion

    The one-page handwritten notes are no longer accepted during the exam. Last year's experience showed some students copying chatGPT codes to the notes without properly working them out. The Statistics Study Guide linked with the VLE contains everything needed to answer VLE exam questions and will be available at the exam.

    Examination

    The course has a total of 3 LADOK credits. The grade for the course is based on the results of the examination on Thursday, 7th of May 2026, 9-11am in SB-D080 lab, taken within the VLE environment. In order 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% and above.

    The resit examination will be announced in due time.

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    Examination procedures

    The exam consists of the same type of questions used in the VLE studies. You do not need to register centrally for the exam, but to book yourself via VLE during the registration.  You will be provided an access link to the exam when it starts. Matlab and the course Study Guide will be available during the exam.

    At the exam, you should be able to show valid identification.

    After the exam has been graded, you can see your results in Ladok.

     Any complaints about the marking must be first 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 Chalmers student portal.

    Student representatives

    TBA

    Minutes of Staff-Student Representatives Meeting

Minutes of the meetings will appear here

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Program

The program can be found on the Detailed program page.