Is there a near-exhaustive summary of statistical procedures? What I want to know
Are there any near-exhaustive (... and preferably free) informational resources that summarize statistical tests/procedures? Please take 'near-exhaustive' to approximately mean "has most of the statistical methods you've heard of". An example of the sort of summary information I would hope for would include usable data types of the variables (ex. ordinal, continuous), assumptions (ex. dependence, normality, or homoscedasticity), and number of dependent variables.
Why do I want to know
I want to be able to have a large resource to consult for deciding what type of analysis I should use for a dataset and experimental design. The idea being that I could then go learn the details of any procedure in this summary that appeared most promising for my current data analysis needs.
What I've been doing
As if I couldn't believe statistics was a huge topic, although I do believe it, I've been reading from a variety of websites (most-frequently wikipedia and university pages) on different methods of statistical analysis out there. I've been building a spreadsheet with each entry being a distinct analysis, and the fields being the properties or assumptions I can find on that analysis. This is proving to be a very difficult task, and resultantly my table is not as complete as I would like. I feel like such a summary would be a useful tool for both noob and veteran alike. 
The closest I have found is the NIST/SEMATECH e-Handbook for Engineering Statistics, but there are plenty of methods that even a noob like me has heard of that are not in this document (http://www.itl.nist.gov/div898/handbook/index.htm). Although it is not as complete as I would like, I will caveat I do find its scope impressive.
 A: Seems like a mundane answer, but Wikipedia is an outstanding source without a finnish line.  I have created for myself several "Wikipedia books" that consist of aggregated Wikipedia articles on specific quantitative subjects.  The results are self-customized world class textbooks-equivalent on any statistical or quantitative domain of your choosing.  And, whenever you are intested in a new methodology you can add it to your Wikipedia book and it essentially creates a new chapter for it, including the article.  Just learn how to create those Wikipedia pdf files that you turn into a book and you are set.
The above, I think, is a highly underutilized capability of Wikipedia.  Although it is really easy to do, I don't know of anyone else that has used this method to boost their learning by creating easily worldclass reference material.
Additionally, depending on what software you use those may have really interesting documentation.  Software like SAS, SPSS, Matlab, STATA, XLStat have documentation that represents rich references on the subject.  If you are an R user, it also has a ton of reference material on an evergrowing number of quantitative methods.  And, it is free (a marked advantage vs. the commercial proprietary software mentioned earlier).        
