Mathematical Statistics, 6 credits

Matematisk statistik, 6 hp

TAMS27

The course is disused. Replaced by TAMS42.

Main field of study

Mathematics Applied Mathematics

Course level

First cycle

Course type

Programme course

Examiner

Jörg-Uwe Löbus

Director of studies or equivalent

Ingegerd Skoglund

Education components

Preliminary scheduled hours: 47 h
Recommended self-study hours: 113 h

Possible deviation from course syllabus/programme syllabus

ECV = Elective / Compulsory / Voluntary

Course offered for		Semester	Period	Timetable module	Language	Campus	ECV
6CDDD	Computer Science and Engineering, M Sc in Engineering	4 (Spring 2017)	2	2	Swedish	Linköping, Valla	C

Main field of study

Mathematics, Applied Mathematics

Course level

First cycle

Advancement level

G2X

Course offered for

Computer Science and Engineering, 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

Series, Integral calculus (one and two variables), Linear algebra, differential calculus.

Intended learning outcomes

The course gives an introduction to mathematical modelling of experiments where the outcome is influenced by random factors. It is directed towards topics required for application in computer engineering. By the end of the course, the student should

understand basic concepts in probability theory
be able to set up relevant probability models for random experiments
apply the techniques in the course to analyse these models

Course content

Sample space, events and probabilities. Elementary combinatorial probability. Conditional probability and independence. Discrete random variables and probability distributions, expectation and variance. Binomial, Poisson distributions etc. The Probability Generating Function. Continuous Random Variables. Uniform, Exponential and Normal Distributions. Functions of random variables. Moment Generating Function. Simulating a Random Variable. Sampling. The Law of Large Numbers. The Central Limit Theorem. Stochastic Processes: The Poisson Process, introduction to Markov chains.

Teaching and working methods

Teaching consists of lectures, tutorials and a computer laboratory.

Examination

TEN2

Written examination

6 credits

U, 3, 4, 5

Grades

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

Other information

Supplementary courses:
The course prepares the student for courses in:
Queueing Theory, which develops the queueing models and their applications.
Bayesian Networks, which discusses graphical modelling and algorithms for updating probabilities in causal networks.

Department

Matematiska institutionen

Director of Studies or equivalent

Ingegerd Skoglund

Examiner

Jörg-Uwe Löbus

Course website and other links

http://courses.mai.liu.se/GU/TAMS27

Education components

Preliminary scheduled hours: 47 h
Recommended self-study hours: 113 h

Course literature

Sheldon Ross: A First Course in Probability, Pearson International Edition. Exempelsamling utgiven av institutionen. Institutionens formelsamling i matematisk statistik. [Handbook of formulas published by the department.]

Code	Name	Scope	Grading scale
TEN2	Written examination	6 credits	U, 3, 4, 5

Regulations (apply to LiU in its entirety)

The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.

LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.

Student rights and obligations (login required)
Linköping University common rules and regulations (in Swedish)

Course literature is preliminary.

Download

Download course literature list as PDF

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize

		I	U	A
1. DISCIPLINARY KNOWLEDGE AND REASONING
	1.1 Knowledge of underlying mathematics and science (G1X level)	X	X	X
	1.2 Fundamental engineering knowledge (G1X level)
	1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)
	1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)
	1.5 Insight into current research and development work
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
	2.1 Analytical reasoning and problem solving	X	X	X
	2.2 Experimentation, investigation, and knowledge discovery	X	X
	2.3 System thinking
	2.4 Attitudes, thought, and learning		X
	2.5 Ethics, equity, and other responsibilities		X
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
	3.1 Teamwork			X
	3.2 Communications			X
	3.3 Communication in foreign languages			X
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
	4.1 External, societal, and environmental context
	4.2 Enterprise and business context
	4.3 Conceiving, system engineering and management
	4.4 Designing
	4.5 Implementing
	4.6 Operating
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS
	5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development
	5.2 Economic conditions for knowledge development
	5.3 Identification of needs, structuring and planning of research or development projects	X	X
	5.4 Execution of research or development projects
	5.5 Presentation and evaluation of research or development projects

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