The core outcome from this course is to recognise that most statistical methods you use can be understood under a single framework, as special cases of (generalised) linear models. Learning statistical methods in a systematic way, instead of as a "cookbook" of different methods, enables you to take a systematic approach to key steps in analysis (like assumption checking) and to extend your skills to handle more complex situations you might encounter in the future (random factors, multivariate analysis, choosing between a set of competing models).
This three-day short course is aimed at applied researchers with prior experience using R and familiar with introductory statistics tools - you should know about the t-test, linear regression, analysis of variance and know something about orthogonal and nested designs. If you have not used R before, we strongly recommend you learn basic features of R and how to use the RStudio interface to R before this course. If you need to revise introductory statistics material, you should attend the Introductory Statistics for Researchers course (see below) earlier in August 2019, and then take this regression course later, as the material in the Introductory Statistics for Researchers course is taken as assumed knowledge for this regression course.
An outline of topics included in this regression course is below (click the "+" on the right).
Requirements: You will need to bring your own laptop! We will sort out internet access for you.
Duration: 3 days, 9.00 am to 5.00 pm daily
Location: UNSW Business School (E12), Level 1, Room 119, UNSW Kensington Campus