COURSE SYLLABUS

Mathematical Statistics 7.5 credits

Matematisk statistik
First cycle, S0001M
Version
Course syllabus valid: Autumn 2020 Sp 1 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.

Syllabus established
by 06 Sep 2007

Last revised
by HUL Niklas Lehto 08 Jun 2020

 Education level First cycle Grade scale G U 3 4 5 Subject Mathematical Statistics Subject group (SCB) Mathematical Statistics Main field of study Industrial and Management Engineering, Engineering Physics and Electrical Engineering

Entry requirements

In order to meet the general entry requirements for first cycle studies you must have successfully completed upper secondary education and documented skills in English language and Calculus M0029M, Linear Algebra and Calculus M0030M and Linear Algebra or equivalent.

Selection

The selection is based on 1-165 credits.

Course Aim
The student shall, after completion of the course - be able to define descriptive statistics for distributions and data, such as measures of location and dispersion; be familiar with basic concepts from probability and statistical theory as well as understand the concept of a statistical model. - be able to use statistical software for processing and analyzing; construct simple statistical models for experiments and describe the applicability of certain standard models, including the multiple linear regression model; be able to apply the statistical methods for analysis that the course treats. – be ale to assess when statistical methods are useful; be able to estimate how uncertainty affects conclusions and quantify risks in terms of error probabilities.

Contents
Descriptive statistics and exploratory data analysis: The most common methods are treated. Probability theory: Basic concepts and models for random phenomena, the most common distributions, the central limit theorem. Statistical inference: point-, interval estimation and hypothesis testing in non-parametric situations and for the most common distributions, methods for comparing two populations, the use of statistical software. Regression analysis: Simple and multiple linear regression with emphasis on the interpretation of results.

Realization
Regular lectures, collaborative learning in small groups, laboratory assignments, peer group assessments of the reports of the laboratory assignments, and web-based quizzes (webbquizzes) that are done continuously throughout the course.

Examination
For grade 3: laboratory assignments and approved first part of the written examination. Grades 4 and 5 require  that the more detailed, second part of the exam is written. Voluntary webquizzes can give bonus points to the first part of the written exam.

Remarks
This course cannot be included in a study program in combination with the course S0008M.

Examiner

Transition terms
The course S0001M is equal to MAM800

Literature. Valid from Autumn 2020 Sp 1 (May change until 10 weeks before course start)
K. Vännman: Matematisk statistik, third edition. Complementery coursematerial are posted in the course room in Fronter.

Course offered by
Department of Engineering Sciences and Mathematics

Modules