Mathematical Statistics, First Course, 4 credits (TAMS79)

Matematisk statistik, grundkurs, 4 hp

Main field of study

Mathematics Applied Mathematics

First cycle

Programme course

Jörg-Uwe Löbus

Director of studies or equivalent

Ingegerd Skoglund
Course offered for Semester Period Timetable module Language Campus VOF
6CIII Industrial Engineering and Management, M Sc in Engineering 3 (Autumn 2017) 2 3 Swedish Linköping o
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Spanish 3 (Autumn 2017) 2 3 Swedish Linköping o
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - French 3 (Autumn 2017) 2 3 Swedish Linköping o
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Japanese 3 (Autumn 2017) 2 3 Swedish Linköping o
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - German 3 (Autumn 2017) 2 3 Swedish Linköping o
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Chinese 3 (Autumn 2017) 2 3 Swedish Linköping o

Main field of study

Mathematics, Applied Mathematics

First cycle

G1X

Course offered for

• Industrial Engineering and Management, M Sc in Engineering
• Industrial Engineering and Management - International, M Sc in Engineering

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

Algebra and calculus, especially differentiation, integration, multiple integration and series.

Intended learning outcomes

The course gives an introduction to the mathematical modelling of random experiments, with a special emphasis on applications in science, technology, and economics. After completing the course the student will be expected to be able to:

• identify experiments where the result is influenced by random factors.
• describe the basic concepts and theorems of probability theory, e.g., random variable, density function, and the law of large numbers.
• construct suitable probabilistic models for random experiments.
• compute important quantities in probabilistic models, e.g., probabilities and expectations.
• construct and analyse probabilistic models for certain time-dependent randomly varying quantities, e. g. in form of time discrete Markov chains.
• follow a basic course in statistics.

Course content

Sample space, events and probabilities. Combinatorics. Conditional probabilities and independent events. Discrete and continuous random variables, their probability distributions, expectations and variances. Normal, exponential, binomial, poisson distributions etc. Functions of random variables. Multidimensional random variables. Law of large numbers and the central limit theorem. Poisson processes. Time discrete Markov chains.

Teaching and working methods

Lectures and tutorials.

Examination

 TEN1 Written examination U, 3, 4, 5 4 credits

Four-grade scale, LiU, U, 3, 4, 5

Other information

 Supplementary courses: Mathematical Statistics, second course. Queueing Theory. Probability Theory, second course. Stochastic Processes. Production and Operations Management. Financial Markets and Instruments.

Department

Matematiska institutionen

Director of Studies or equivalent

Ingegerd Skoglund

Examiner

Jörg-Uwe Löbus

http://courses.mai.liu.se/GU/TAMS79

Education components

Preliminary scheduled hours: 40 h
Recommended self-study hours: 67 h

Course literature

G. Blom, J. Enger, G. Englund, J. Grandell, L. Holst: Sannolikhetsteori och statistikteori med tillämpningar. Studentlitteratur.
Institutionens formelsamling i matematisk statistik.
G. Blom, J. Enger, G. Englund, J. Grandell, L. Holst: Sannolikhetsteori och statistikteori med tillämpningar. Studentlitteratur. <br>Institutionens formelsamling i matematisk statistik.