An Introduction to Modelling in R - 2 day course presented by Paul Baxter and Andrew Blance (University of Leeds)
The purpose of this course is to introduce participants to the R environment for statistical computing. Day 1 focuses on entering, working with and visualising data in R. Day 2 focuses on regression modelling in R, including linear, general linear, logistic and survival models. Participants can either register for both days, or for either Day 1 or Day 2, depending on their background and interests.
The course has an applied focus. Each topic is introduced by the course leaders using examples and practical demonstration in R (approximately 40% of course time). Participants will then be invited to work through example exercises in R with support from the course leaders (approximately 60% of course time).
Topics covered in Day 1 include: entering data and obtaining help in R; working with data in R; summarising data graphically and numerically in R; basic hypothesis tests in R.
Topics covered in Day 2 include: the linear model in R; the general linear model in R; logistic regression in R; survival models in R.
Day 1 will be ideally suited to those:
familiar with basic statistical methods (e.g. t-tests, boxplots) and who want to implement these methods using R.
who have used menu-driven statistical software (e.g. SPSS, Minitab) and who want to investigate the flexibility offered by a command line package such as R.
Day 2 will be ideally suited to those:
already familiar with basic statistical methods in R and who wish to extend their knowledge to regression involving multiple predictor variables, binary, categorical and survival response variables.
familiar with regression methods in menu-driven software (e.g. SPSS, Minitab) and who wish to migrate to using R for their analyses.
For more information and to register, please visit http://www.rss.org.uk/courses
You may leave the list at any time by sending the command
to [log in to unmask], leaving the subject line blank.