The course provides a broad introduction to advanced statistical modeling tools. Starting from the fundamental linear regression models, we investigate modelling of non-linear (but parametric) relationships between explanatory and response variables. We then consider the Generalized Linear Models (GLM), which model a function of the expected value, rather than the expected value itself. This methodology includes binary response (0/1) data modelling and the modelling of count and proportion data. We further investigate the Generalized Additive Models (GAM) with the response being modelled in terms of explanatory variables without explicitly assumed parametric relationship. We also incorporate the GAM methodology in the GLM setting, allowing for the modelling of various types of responses with complex structure dependencies on explanatory variables. We also show how we can use Bootstrap methodology to perform inference and tests as an alternative to standard statistical procedures.
In a degree, this course may not be included together with another course with a similar content. If unsure, students should ask the Director of Studies in Mathematics and Mathematical Statistics. The course can also be included in the subject area of computational science and engineering.
The course requires a total of 90 ECTS including courses in Mathematical Statistics minimum 12 ECTS and a course in basic Computer Programming or equivalent knowledge. Proficiency in English equivalent to Swedish upper secondary course English 5/A. Where the language of instruction is Swedish, applicants must prove proficiency in Swedish to the level required for basic eligibility for higher studies.
Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.
Application deadline was
16 October 2017.
Please note: This second application round is intended only for EU/EEA/Swiss citizens.