This page is currently a work-in-progress. I am not a mathematician, statistician, biostatistician, or even really that good with statistics. What I have done is cobbled together enough knowledge from various colleagues and online sources that I am reasonably competent with common procedures and have the know-how to slowly trouble-shoot my way through new tests. Both general statistics and R have learning curves that approximate cliffs and present significant challenges - seriously, how many biologists do you know that have either "tried" or "have been meaning to learn" R? However, in my experience, learning statistics and R in tandem can actually help make the concepts in both more clear. Statistics can be tricky and unintuitive for those without a strong math background. R is more akin to pure programming than the graphical interfaces of Excel and SPSS. My hope here is that by explaining things in plain English (actually plain English, not statistics-plain) I can help make data analysis more approachable.
I have several goals for this page. I intend to make as many of my data sets and as much of the associated R code publicly available as possible. My publication code files are fairly heavily commented, making them nearly ready-made guides based around real-world examples. I'm not a statistician, and thus not perfect; open sharing will also allow other researchers access to my data and code and aid with critiques of my methods. This will hopefully encourage other researchers to share their raw data.
I have several goals for this page. I intend to make as many of my data sets and as much of the associated R code publicly available as possible. My publication code files are fairly heavily commented, making them nearly ready-made guides based around real-world examples. I'm not a statistician, and thus not perfect; open sharing will also allow other researchers access to my data and code and aid with critiques of my methods. This will hopefully encourage other researchers to share their raw data.