9-20 July 2012 (Stellenbosch) Introduction to Statistics and its Applications in Biology. 2-week Course. Course completed.

Posted on Sun, Jul 08 2012 23:00:00
Course completed

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The South African Centre for Epidemiological Modelling and Analysis (SACEMA), in association with the University of KwaZulu-Natal (UKZN) and the University of Ghent, Belgium, invites applications from suitably qualified candidates to attend the above course. The purpose of the course is to train Southern African students, health workers and professionals in the basic concepts and the most commonly applied methods of biostatistics, and so contribute to capacity building in this important field.

Level 1. This beginners course will teach students the basics of statistics, including: sampling, types of variables, frequency distributions, graphical methods, measures of central tendency and dispersion, and estimation. Students will gain experience with exploratory data analysis by learning how to do hypothesis tests for different types of data and samples. Students will also be provided with a basic introduction to simple linear regression. All lessons will be reinforced with practical sessions using the statistical package, R. The Level 1 course will not assume prior knowledge of programming in R, but some introductory R-tutorials will be made available in advance, and participants will be strongly advised to work on these before coming.

Level 2. This course will assume students have done at least one course in statistics and will focus on statistical methods for modelling the association between risk factors and response. It will include: Generalized linear models with specific reference to linear, logistic and poison regression;  The analysis of time-to-event outcomes, including the Kaplan-Meier method for constructing and comparing survival distributions and the Cox Proportional Hazards model;  Generalized Estimating Equations and Generalized Linear Mixed effect models for the analysis of longitudinal data. All lessons will be reinforced with practical sessions on data drawn from biology and medicine, using the statistical package, R. A knowledge of basic statistics is a requirement for Level 2. Some previous exposure to programming in R is recommended, though the course will start with a short review of how to use R for simple statistics and programming.