1 Oct
4 Nov


Statistics III: Regression analysis, 4HP

The Ph.D. course will be given in Umeå 1 October - 4 November 2019.

Prior knowledge

Statistics I: Basic Statistics or equivalent

Objective, including learning outcomes

The objective of the course is to give an overview of linear, nonlinear and nonparametric regression. On completion of the course, the student will be able to: 
• specify regression models including conditions and assumptions
• select an appropriate regression model for a given problem
• carry out a regression analysis in the statistical software R 
• interpret and evaluate results correctly and draw reasonable conclusions
• clearly and concisely communicate results and conclusion


The course will cover the following topics:
• Simple linear regression.
• Multiple linear regression.
• Nonlinear models. 
• Nonparametric regression and generalized additive models (GAM).
• Analysis of residuals.



Time: 2019-10-01 - 2019-11-04
City: Umeå
Last signup date: 20 September 2019
Additional info:

Applications are to be sent by e-mail to Magnus Ekström and should contain the following information: 

Name of applicant • Personal identification number (personnummer) • Academic affiliation.

Course site @slu

 Course literature
Main textbook: Samprit Chatterjee & Jeffrey S. Simonoff (2013). Handbook of Regression Analysis. Hoboken: John Wiley & Sons. (Available at https://ebookcentral.proquest.com/lib/slub-ebooks/reader.action?docID=1108688)

Additional reading: Samprit Chatterjee & Ali S. Hadi (2012). Regression Analysis by Example, 5th Ed. Hoboken: John Wiley & Sons. ​(Available at https://ebookcentral.proquest.com/lib/slub-ebooks/detail.action?docID=918623​)