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Links to other Demos, Statistics sites, etc.

Google and Google Scholar (of course)

Google Scholar

Here is the site for our textbook. In a addition to lots of great online information, you can also download the data for all of the homework problems.

The statistical package R is quickly becoming the language of statistical computing (for good reason). It's not pointy-and-clicky though, and that scares some people. Some good but gentle introductions are:
-This online R tutorial at
-This brief introduction for beginners by ecologist (and non-statistician) Duncan Golicher.
Once you start getting comfortable with R, you'll find this reference card very handy.

UT offers statistical consulting and offers short courses and tutorials on sundry statistical packages through The Division of Statistics and Scientific Computing . You're tuition and fees are paying for it, so you might as well use it! They could potentially be a big help throughout your graduate career here. Surf the site - in particular, look under consulting, courses, for graduate students, and software.

The Rice Virtual Statistics Laboratory ( RVSL ) is a nice site from Rice University. In particular, check out the interactive demonstrations .

Another really nice demo site is rpsychologist ( RPsychologist ). It seems to get updated regularly and I really like the interactive demos.

The best all-around online statistics site for students I have seen is by StatSoft (the company behind STATISTICA software). Give it a browse. It is pretty impressive.

As I have mentioned (or will mention) in class many times, not nearly enough attention is paid to graphing data. Here is an awesome site about data visualization. Please take some time to browse though it. Treat yourself to some of the "darts" - the worst graphs ever to make it into print. There is also a nice blog about bad graphs called Graphic Violence that is worth checking in on from time to time.

The calculation of power is very important. In simple situations, a sketch on a napkin will tell you what you need to know, but this isn't possible when things get more complicated. One software solution is G*Power . In addition to being a useful utility, I think it is very helpful in wrapping your head around what power, alpha, etc. are. has a nice searchable glossary and many links to free software. (you have to register, but it is free)

Richard Lowry at Vasser College has a good webtext , which is meant to be a companion site to his website for statistical computation . From what I have seen, the webtext is also a nice stand-alone resource, and the computation website contains some informative demonstrations.

Finally, be aware that there is a lot - a lot - of stuff out there. Wikipedia has a lot of very good articles, and don't be afraid to use your Google Fu (and please let me know if you find anything link-worthy).