Entry requirements

120 credits including 90 credits in mathematics, including Regression Analysis. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

On completion of the course, the student should be able to:

• give an account of the sampling strategies for categorical data;
• analyse a two-way contingency table;
• carry out exact inference for a three-way contingency table;
• build and apply logit and loglinear models;
• use R for analysing real data sets;
• be able to interpret the results in practical examples.

Content

Poisson sampling. Binomial sampling. Inference for odds ratio. Chi-squared tests. Fisher's exact test. Partial tables. Cochran-Mantel-Haenszel methods. Exact tests. Models for binary data. Loglinear models for contingency tables. R commands.

Instruction

Lectures and computer sessions.

Assessment

Written examination at the end of the course. Compulsory assignments during the course.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.