Prof Jonathan Jackson COL8.05

This course is available on the MPhil/PhD in Health Policy and Health Economics. This course is available as an outside option to students on other programmes where regulations permit.

This course is available to all research students where regulations permit.

Participants should have studied introductory statistics or quantitative methods before, up to an introduction to descriptive statistics and basic statistical inference. Students with no previous studies in quantitative analysis should take instead Introduction to Quantitative Analysis (MY451). 

Because of the overlaps between these courses, it is not possible to take both this course and either of Introduction to Quantitative Analysis (MY451) or Applied Regression Analysis (MY452) as assessed courses. 

The course is intended for students with some (even if limited) previous experience of quantitative methods or statistics. Using examples from psychological research, it covers first a review of the foundations of descriptive statistics and statistical inference, in the context of the analysis of two-way contingency tables and comparisons of means between two groups. The main topic of the course is linear regression modelling and related methods, including scatterplots, correlation, simple and multiple linear regression, and analysis of variance and covariance. An introduction to binary logistic regression modelling is also included. The computer classes give hands-on training in the application of these statistical techniques. Class exercises and homework are carried out using the Stata package.

20 hours of lectures and 10 hours of computer workshops in the MT. 2 hours of lectures in the ST.

Students on this course will have a reading week in Week 6. On-line quizzes will be provided on Moodle to aid revision during the reading week. 

Students will be expected to produce 9 exercises in the MT.

A course pack will be available for download online.

Additional reading: many introductory statistics books are available. But we particularly recommend Alan Agresti and Christine Franklin (2009) Statistics: The Art and Science of Learning from Data, and Alan Agresti and Barbara Finlay (2009, 4th edition) Statistical Methods for the Social Sciences.

Exam (100%, duration: 2 hours) in the summer exam period.

Students are permitted to bring a limited quantity of written notes into the examination.