Mathematical Statistics, First Course, 6 credits

Matematisk statistik, 6 hp

TAMS28

The course is disused.

Main field of study

Mathematics Applied Mathematics

Course level

First cycle

Course type

Programme course

Examiner

Zhengxia Liu

Director of studies or equivalent

Ingegerd Skoglund

Education components

Preliminary scheduled hours: 56 h
Recommended self-study hours: 104 h
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Period Timetable module Language Campus ECV
6CKEB Chemical Biology, M Sc in Engineering 6 (Spring 2017) 1 4 Swedish Linköping C
6CTBI Engineering Biology, M Sc in Engineering 4 (Spring 2017) 1 4 Swedish Linköping C

Main field of study

Mathematics, Applied Mathematics

Course level

First cycle

Advancement level

G2X

Course offered for

  • Engineering Biology, M Sc in Engineering
  • Chemical Biology, 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 matrix algebra, diferentiation, integration and power series.

Intended learning outcomes

The aim of the course is to give an introduction to probability and statistics, i.e. both to introduce theoretical probability models and to provide methods for statistical inference based on observed data. By the end of the course, the student should be able to:

  • describe and use models for phenomena influenced by random factors and calculate probabilities;
  • use random variables and their properties to describe and explain random variation, use a probability mass function or a density function to calculate probabilities, expected values, variances etc;
  • apply an appropriate probabilty model to describe and analyse observed data and draw conclusions concerning interesting parameters by using point estimation, confidence intervals and hypothesis testing;
  • analyse the relationships between two or several variables by using simple or multiple linear regression models and discuss the adequacy of the models;
  • use probability models and statistical methods in applications from science and engineering and evaluate the results;
  • use software for certain types of statistical analyses.

Course content

Probability: Sample spaces, events and probabily. Conditional probability. Independent events. Random variables, expected value, variance and standard deviation; especially normal, exponential, binomial and Poisson distribution. The central limit theorem.
Statistics: Methods for parameter estimation. Confidence intervals in connection with one or several samples from the normal distribution, for proportions, in connection with the Poisson distribution etc. Tests of hypothesis in particular chisquare tests. Simple and multiple linear regression. Histograms.

Teaching and working methods

Teaching consists of lectures, lessons and obligatory computer exercises.

Examination

LAB1Computer Exercises1 creditsU, G
TEN1Written examination5 creditsU, 3, 4, 5

Grades

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

Other information

Supplementary courses: Biostatistics, Signal and Image Processing.

Department

Matematiska institutionen

Director of Studies or equivalent

Ingegerd Skoglund

Examiner

Zhengxia Liu

Course website and other links

http://courses.mai.liu.se/GU/TAMS28

Education components

Preliminary scheduled hours: 56 h
Recommended self-study hours: 104 h

Course literature

Montgomery, D.C., Runger, G.C., Hubele, N.F., Engineering Statistics, 5th Edition Formel- och tabellsamling i matematisk statistik utgiven av matematiska institutionen. Exempelsamling.
Code Name Scope Grading scale
LAB1 Computer Exercises 1 credits U, G
TEN1 Written examination 5 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. 

Montgomery, D.C., Runger, G.C., Hubele, N.F., Engineering Statistics, 5th Edition Formel- och tabellsamling i matematisk statistik utgiven av matematiska institutionen. Exempelsamling.

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

I = Introduce, U = Teach, A = Utilize
I U A Modules Comment
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

                            

This tab contains public material from the course room in Lisam. The information published here is not legally binding, such material can be found under the other tabs on this page.

There are no files available for this course.