Applied Multiple Regression and ANOVA

The course is included in the program PHD in science.It may be taken as a singular course and is also available for inbound exchange students

The course is intended for students who collect and analyse data, and who need to know more about the use of statistics within their own field. The course is normally included in Ph.d. programs in other subjects than statistics and mathematics. Students attending the course should be familiar with the concepts of random variables and distributions, normal distribution, estimation, confidence interval and hypothesis testing.

Subjects covered in this course are: Multiple linear regression analysis. Correlations. One- and two-way analysis of variance. Understanding the regression model and the assumptions for the model. Testing significance of the variables. Determining a best-fitting model and evaluate the model. Using R2, the multiple correlation coefficient. Examples and exercises with real data from several areas using statistical software.

PhD students or holders of a Norwegian master´s degree in Sceince of five years or 3+ 2 years (or equivalent) may apply. In your educational background you need statistical courses of at least 30 ECTS credits which includes a thorough discussion of statistical methods and principles.

PhD students from other universities must upload a document from their home institution stating that they are registered PhD students. This group of applicants does not have to prove English proficiency and are exempt from semester fee.

Holders of a Master´s degree must upload a Master´s Diploma with Diploma Supplement / English translation of the diploma. Applicants from listed countries must document proficiency in English. For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see the following document:

Proficiency in english - PhD level studies

PhD students at UiT The Arctic University of Norway register for the course through StudentWeb.

External applicants apply for admission through SøknadsWeb.

All external applicants have to attach a confirmation of their status as a PhD student from their home institution. Students who hold a Master of Science degree, but are not yet enrolled as a PhD-student have to attach a copy of their master's degree diploma. These students are also required to pay the semester fee.

More information regarding PhD courses at the Faculty of Science and Technology is found here.

Knowledge - The candidate has knowledge about:

• The assumptions for using regression- and analysis of variance.
• The two types of independent variables (covariates): measurement- and nominal (categorical) variables.
• The concept of confounding.
• The concept of interaction between independent variables.
• Polynomials and transformation of variables.
• Criteria (R2, F, Mallows’ Cp) and strategies for selecting the best model (forward, backward, stepwise and best subset).
• One- and two-way analysis of variance, balanced design, fixed and/or random factors.
• The general linear model as a framework for multiple regression- and anova models.

Skills - The candidate can:

• Prepare data and perform regression analysis using a statistical software.
• Use regression diagnostics, such as analysis of residuals to identify possible outliers, check the model assumptions and address problems with collinearity.

General expertise - The candidate can:

• Choose a reasonable linear model to analyse his/her data sets.
• Explain the regression results to a person who is not familiar with statistical thinking.
• Interpret regression results. Understand the significance and the importance of the selected independent variables in explaining the response variable.

Language of instruction and examination

This course is open for inbound exchange student who meets the admission requirements, including prerequisites. Please see the Admission requirements" and the "Prerequisite" sections for more information.

Do you have questions about this course? Please check the following website to contact the course coordinator for exchange students at the faculty: https://en.uit.no/education/art?p_document_id=510412