| NMAC18 | Statistical Methods in Mathematical Models, 9 ECTS credits. /Statistiska metoder för matematiska modeller/ |
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Prel. scheduled
hours: 48 |
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Area of Education: Science Subject area: Mathematics |
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| Advancement level
(G1, G2, A): G2
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| Aim: The course is intended to develop skills in mathematical and probabilistic modelling of biological phenomena, and teach statistical principles and methods when applying these models to empirical data. The course discusses various methods for estimating parameters in a model and checking the adequacy of the model, the assumptions under which a model may be used and how to choose between different mathematical models for the same phenomenon. The methods are applied to models in biology and chemistry. By the end of the course, the student ought to know something about:
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| Prerequisites: (valid for students admitted to programmes within which the course is offered) TAMS35, TAMS07, NMAB06 Mathematical Statistics, part 1, or a similar course. 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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| Organisation: The teaching consists of lectures (24 hours), problem solving (12 hours) and computer sessions (24 hours). |
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| Course contents: Programming in MATLAB. Introduction to probabilistic modelling in biology and ecology, models and parameter estimation for spatial phenomenon: use of the probability generating function. Survival distributions, dependence on environmental variables, survival curves of populations. Regression analysis: multiple linear and generalized linear models, including logistic regression. Bootstrap methods. Nonlinear methods. The Lotka Volterra model. |
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| Course literature: A Compendium containing lecture notes, examples and computer exercises (required). |
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| Examination: | ||||
| Project work |
6 p |
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9 ECTS |
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Course language is Swedish/English. Department offering the course: MAI. Director of Studies: Eva Enqvist Examiner: John Noble Course Syllabus in Swedish |
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