Mathematical Statistics, First Course, 6 credits
Matematisk statistik, 6 hp
TAMS28
Main field of study
Mathematics Applied MathematicsCourse level
First cycleCourse type
Programme courseExaminer
Zhengxia LiuDirector of studies or equivalent
Ingegerd SkoglundEducation components
Preliminary scheduled hours: 56 hRecommended self-study hours: 104 h
Course offered for | Semester | Period | Timetable module | Language | Campus | ECV | |
---|---|---|---|---|---|---|---|
6CKEB | Chemical Biology, M Sc in Engineering | 6 (Spring 2017) | 1 | 4 | Swedish | Linköping, Valla | C |
6CTBI | Engineering Biology, M Sc in Engineering | 4 (Spring 2017) | 1 | 4 | Swedish | Linköping, Valla | C |
Main field of study
Mathematics, Applied MathematicsCourse level
First cycleAdvancement level
G2XCourse 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
LAB1 | Computer Exercises | 1 credits | U, G |
TEN1 | Written examination | 5 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Other information
Supplementary courses: Biostatistics, Signal and Image Processing.
Department
Matematiska institutionenDirector of Studies or equivalent
Ingegerd SkoglundExaminer
Zhengxia LiuCourse website and other links
http://courses.mai.liu.se/GU/TAMS28Education components
Preliminary scheduled hours: 56 hRecommended 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.
Note: The course matrix might contain more information in Swedish.
I | U | A | Modules | Comment | ||
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1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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X
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1.2 Fundamental engineering knowledge (G1X level) |
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1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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1.5 Insight into current research and development work |
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2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
2.1 Analytical reasoning and problem solving |
X
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X
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X
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2.2 Experimentation, investigation, and knowledge discovery |
X
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X
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2.3 System thinking |
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2.4 Attitudes, thought, and learning |
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X
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2.5 Ethics, equity, and other responsibilities |
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X
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3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
3.1 Teamwork |
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X
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3.2 Communications |
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X
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3.3 Communication in foreign languages |
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X
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4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
4.1 External, societal, and environmental context |
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4.2 Enterprise and business context |
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4.3 Conceiving, system engineering and management |
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4.4 Designing |
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4.5 Implementing |
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4.6 Operating |
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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 |
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5.2 Economic conditions for knowledge development |
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5.3 Identification of needs, structuring and planning of research or development projects |
X
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X
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5.4 Execution of research or development projects |
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5.5 Presentation and evaluation of research or development projects |
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