Statistics B - Regression analysis and analysis of variance
I många sammanhang vill man studera samband mellan olika variabler och dra eventuella slutsatser. I kursen introduceras du till de kraftfulla och allmängiltiga statistiska metoder som finns inom regressions- och variansanalys. Du får också en överblick över vanliga försöksdesigner.
Vid praktiskt arbete med data är det viktigt att kunna välja en lämplig metod för ett givet problem, och att kunna utvärdera resultatet från en metod och dra rimliga slutsatser. I kursen arbetar du med frågeställningar kring data i datorövningar och tillämpar mot slutet dina kunskaper i ett eget litet projekt.
Additional course evaluations for MS0071
Academic year 2020/2021Statistics B - Regression analysis and analysis of variance (MS0071-20162) 2020-11-02 - 2020-12-02
Academic year 2019/2020Statistics B - Regression analysis and analysis of variance (MS0071-20156) 2019-11-01 - 2019-12-03
MS0071 Statistics B - Regression analysis and analysis of variance, 7.5 CreditsStatistik B - Regressions- och variansanalys
Education cycleBachelor’s level
Advanced study in the main fieldFirst cycle, course specialisation cannot be classified(GXX)
Prior knowledge120 credits in the first cycle
5 credits basic statistics
ObjectivesThe objective of the course is to give an overview of methods within the range of general linear models, such as regression analysis and analysis of variance. On completion of the course the student will be able to:
• describe general linear models, such as regression and ANOVA models, including conditions and assumptions
• select an appropriate general linear model for a given experimental or study design
• carry out a regression or ANOVA analysis in the statistical software R
• interpret and evaluate results correctly and draw reasonable conclusions
• clearly and concisely communicate results and conclusions
ContentThe course is built on lectures and computer exercises, as well as a project. The main components are as follows:
Part 1 (6 hp)
• Simple linear regression.
• Multiple linear regression.
• Analysis of variance with one or more fixed and random factors.
• Analysis of covariance, dummy variable coding and the general linear model.
• Analysis of residuals.
• Some extensions or alternatives to models if assumptions for the base models are not fulfilled, e.g. nonparametric methods, nonlinear models and models for data that are not independent.
Part 2 (1.5 hp)
Project work either alone or in a group.
Formats and requirements for examinationPart 1
- Passed examination in written form. Grade U, 3, 4, or 5 are given.
- Passed project report and passed oral presentation at mandatory seminar. Discussions of other groups’ reports can also be part of the examination. Reports, oral presentations, discussions and presence at seminars are only graded with Pass (G) or Fail (U).
- If the student fails a test, the examiner may give the student a supplementary assignment, provided this is possible and there is reason to do so.
- If the student has been granted special educational support because of a disability, the examiner has the right to offer the student an adapted test, or provide an alternative assessment.
- If changes are made to this course syllabus, or if the course is closed, SLU shall decide on transitional rules for examination of students admitted under this syllabus but who have not yet passed the course.
- For the examination of a degree project (independent project), the examiner may also allow the student to add supplemental information after the deadline. For more information on this, please refer to the regulations for education at Bachelor's and Master's level.
- The right to take part in teaching and/or supervision only applies to the course date to which the student has been admitted and registered on.
- If there are special reasons, the student may take part in course components that require compulsory attendance at a later date. For more information on this, please refer to the regulations for education at Bachelor's and Master's level.
Additional informationThis course overlaps with the following courses given at SLU:
ST0058 Statistik för ekonomer, 15 hp
MS0064 Variansanalys, 5 hp
HV0131 Avel 1 (moment variansanalys)
HV0132 Avel 2 (moment variansanalys)