The International Environmetrics Society (TIES) and the Queensland University of Technology (QUT) will be jointly hosting two short courses on February 2-4, 2015 at the QUT Gardens Point Campus in Brisbane:
Please see the website (http://wired.ivvy.com/event/TSC15/) for additional information about the courses, venue, and registration fees.
Practical Bayes for Beginners
Professor Kerrie Mengersen, Queensland University of Technology
This three-day course introduces the practicing statistician to Bayesian analysis. The course is strongly practical, with emphasis on understanding the fundamental concepts, modelling in a Bayesian context, using MCMC and ‘doing’ Bayesian analysis via the software packages R and WinBUGS. Attendees will gain a basic understanding the fundamental concepts, modelling in a Bayesian context, using MCMC and ‘doing’ Bayesian analysis via the software packages R and WinBUGS. Participants will be introduced to a range of models for describing complex data, including mixtures, spatio-temporal models, meta-analysis and Bayesian networks, and the application of these models to real problems in health and ecology.
Advanced R for Environmental Scientists
Dr Bill Venables, CSIRO
R is rapidly becoming the leading programming language in statistics and data science, with more than 2 million users worldwide and more than 4000 contributed packages. The focus of the short course will be on using R efficiently and effectively for data exploration, statistical modelling, and graphics, with a focus on environmental and ecological applications. Attendees will gain a better understanding of object orientation modes in R; mixed-effect extensions to linear, generalized linear and non-linear regression models; and building predictors using various tools from Machine Learning, such as classification and regression trees, boosting and bagging, random forests and similar approaches. Participants will also be given an introduction to using compiled code in R (Rcpp and C++), multicore programming (parallel and allied packages), package construction using RStudio and roxygen2, and reproducible research using RMarkdown and other tools.
