Applied logistic regression, spring 2015


Juha Alho, professor


This course covers the statistical modelling of binary outcomes using regression techniques. Binary outcome refers to YES/NO answers to such questions as is the respondent ill or not, did the respondent vote for a particular political party or not, did the respondent buy a particular product or not etc.

Typical background characteristics on which the probability of the two possible responses may depend include age, sex, socio-economic status, life style characteristics etc.

In this setting the application of ordinary regression techniques is only partly justified. Among the many models that could be entertained, logistic regression is favored because of its mathematical tractability. A price one has to pay for adopting it (or some other variant) is that the maximum likelihood theory becomes more complicated and the interpretation of the parameters is more complex than in ordinary linear regression.

The course emphasises intuitive understanding rather than mathematical precision. It should be accessible for all doctoral students in social sciences, for example.

R will be used for computation, but no previous familiarity with the program is assumed.

In order to pass the course, the students are expected to complete a set of home work assignments that will be graded, and a small final exam.





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