COURSE SYLLABUS

Probability Theory and Statistics 7.5 credits

Sannolikhetslära och statistik
First cycle, S0008M
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 12 Feb 2010

Last revised
by Niklas Lehto 08 Nov 2019

 Education level First cycle Grade scale G U 3 4 5 Subject Mathematical Statistics Subject group (SCB) Mathematical Statistics Main field of study 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 Differential calculus M0029M, Linear algebra and integral calculus M0030M and Linear algebra M0033M 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, dispersion and dependence; 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 data and use computer simulations to estimate the descriptive quantities in statistical distributions.
Construct simple statistical models for experiments and describe the applicability of certain standard models, including the two-dimensional normal distribution; 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 one and multi-dimensional distributions including the two-dimensional normal distribution, conditional 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. Simulation methods: Introduction to statistical methods of simulation and computation.

Realization
Regular lectures, collaborative learning in small groups, laboratory assignments, peer group assessments of the reports of the laboratory assignments, and web-based quizzes (webquizzes) 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 S0001M.

Examiner
Jesper Martinsson

Literature. Valid from Spring 2018 Sp 4 (May change until 10 weeks before course start)
K. Vännman: Matematisk statistik, second edition. Complementary course material is posted in the digital course room in Canvas.

Course offered by
Department of Engineering Sciences and Mathematics

Modules