Statistical models cheat sheet I was wondering if there is a statistical model "cheat sheet(s)" that lists any or more information:


*

*when to use the model

*when not to use the model

*required and optional inputs

*expected outputs

*has the model been tested in different fields (policy, bio, engineering, manufacturing, etc)?

*is it accepted in practice or research?

*expected variation / accuracy / precision

*caveats

*scalability

*deprecated model, avoid or don't use

*etc ..


I've seen hierarchies before on various websites, and some simplistic model cheat sheets in various textbooks; however, it'll be nice if there is a larger one that encompasses various types of models based on different types of analysis and theories.
 A: Reading "Using Multivariate Statistics (4th Edition) Barbara G. Tabachnick" 
I found these decision trees based on major research question. I think they are quite useful. Following this link you'll find an extract of the book
http://www.psychwiki.com/images/d/d8/TF2.pdf
see pages 29 to 31
A: Here is a collection page:
http://sasdataguru.blogspot.com/2011/05/online-statistics-cheat-sheet.html
A: Do you mean a statistical analysis decision tree? (google search), like this (only with extensions):

(source: processma.com) 
?
BTW, notice that the chart in wrong in that the tests it offers for median are not for median but for rank... (it would be for median if the distribution is symmetrical)
A: I have previously found UCLA's "Choosing the Correct Statistical Test" to be helpful:
https://stats.idre.ucla.edu/other/mult-pkg/whatstat/
It also gives examples of how to do the analysis in SAS, Stata, SPSS and R.
A: Since when is regression an hypothesis test of anything?  If by"regression"why is meant is curve fitting or correlations (pair-wise or multiple) the only "test" is between some relation vs. no relation.  Figures like this own their origin to Siege's l956 book.
