Type of course

Admission requirements

Course content

The course is intended for students who collect and analyze data, and who need to know more about the use of statistics within their own field. Students attending the course should be familiar with the concepts of random variables and distributions, normal distribution, estimation, confidence interval and hypotesis testing.

This course teaches the following: 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.Evaluating the model. Using R2, the multiple correlation coeffisient. Examples and exercises with real data from several areas using statistical software.

Recommended prerequisites

Objectives of the course

After the course the student should:

• obtain a solid foundation in applied multiple regression analysis and analysis of variance
• be able to make an independent judgment as to whether regression- or analysis of variance is an appropriate method for the present data
• be able to utilize the program package SPSS in analyzing data

In more detail the student should have 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 between independent variables.
• The concept of interaction between independent variables.
• Polynomials and transformations of variables.
• Criteria (R2, F, Mallow's Cp) and strategies for selecting the best model (forward, backward or stepwise)
• Regression diagnostics, such as analyzing residuals to identify possible outliers, checking the model assumptions, colinearity.
• One-way and two-way analysis of variance, balanced design, fixed and/or random factors
• Interpretation of regression results. The significance and the importance of the selected independent variables in explaining the response variable.

Explaining the regression results to a person who is not familiar with statistical thinking.

Language of instruction and examination

Teaching methods

Information to incoming exchange students

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

Recommended reading/syllabus