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Valid for year : 2007
 
TAMS04 Mathematical Statistics, First Course, 4,5 ECTS credits.
/Matematisk statistik /

For:   Fys   KeBi  

 

Prel. scheduled hours: 50
Rec. self-study hours: 70

  Area of Education: Science

Subject area: Mathematics
  Advancement level (G1, G2, A): G1

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 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 the Minitab software for statistical analyses of different kinds.
Prerequisites: (valid for students admitted to programmes within which the course is offered)
Algebra and calculus, especially 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.
Supplementary courses:
TAMS 12 Biostatistics
Organisation:
Teaching consists of lectures, lessons and obligatory computer exercises.
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: Parameter estimation. Confidence intervals in connection with one or several samples from the normal distribution, for proportions etc. Tests of hypothesis in particular chisquare tests. Simple and multiple linear regression. Descriptive statistics.
Course literature:
Montgomery, D.C., Runger, G.C., Hubele, N.F., Engineering Statistics, Second or Third Edition. Compendium with exercises and Handbook of formulas and tables published by the department.
Examination:
Written examination
Computer Exercises
 2,5 p
0,5 p
/
/
4 ECTS
0,5 ECTS
 


Course language is Swedish.
Department offering the course: MAI.
Director of Studies: Eva Enqvist
Examiner: Eva Enqvist
Link to the course homepage at the department


Course Syllabus in Swedish

Linköping Institute of Technology
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Contact: TFK , val@tfk.liu.se
Last updated: 07/09/2009