| TAMS28 |
Mathematical Statistics, First Course, 6 ECTS credits.
/Matematisk statistik /
For:
KeBi
TB
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Prel. scheduled
hours: 56
Rec. self-study hours: 104
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Area of Education: Science
Main field of studies: Mathematics, Applied Mathematics
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Advancement level
(G1, G2, A): G2
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Aim:
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.
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
Algebra and calculus, especially matrix algebra, diferentiation, integration and power series.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Supplementary courses:
Biostatistics, Signal and Image Processing.
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Organisation:
Teaching consists of lectures, lessons and obligatory computer exercises.
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Course contents:
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.
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Course literature:
Montgomery, D.C., Runger, G.C., Hubele, N.F., Engineering Statistics, 4th Edition. Compendium with exercises and Handbook of formulas and tables published by the department.
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Examination: |
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Written examination
Computer Exercises
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5 ECTS
1 ECTS
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Course language is Swedish.
Department offering the course: MAI.
Director of Studies: Ingegerd Skoglund
Examiner: Zhengxia Liu
Link to the course homepage at the department
Course Syllabus in Swedish
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