Ron Sandland recently wrote about the new phenomenon of 'big data' - weighing up the benefits and concerns. Terry Speed reflected on the same issue in a talk earlier this year inGothenburg, Sweeden noting that this is nothing new to statisticians. So what's all the fuss about? Here's another take on the 'big data' bandwagon.
This course will introduce you to the R statistical computing environment (including new graphics capabilities) in the context of
applied statistical modelling and inference. It will provide a refresher on topics such as:
discrete and continuous probability models
the philosophy of statistical inference (hypothesis testing and estimation)
R statistical software - click here to go to the download page.
(Click here to download instructions for installing R and packages used in the course).
Course Materials (zipped file) (17Mb)
Ordination Modelling using R!
The course is a hybrid of lecture/tutorial style instruction and hands-on learning.
Topics may be expanded, collapsed, or skipped depending on the needs of the class and level of comfort with the R software.
The first day will be more instruction based as you are introduced to R and its capabilities.
The second day is basically a 'doing' day with considerable time allocated to using R to work through a series of exercises.
The last day covers a number of important ordination modelling techniques and will be introduced via an interactive 'follow-me' approach using the R packages
here to watch a short video demonstrating
Environmetrics Australia's capabilities for deploying apps powered by the R statistical computing system. (And if you don't know what R is - click