Statistical analysis flowchart implementation in R I have seen lots of flowcharts describing the different questions you should ask yourself when doing statistical analysis and the corresponding tests you should run based on your answer. For instance, you can find some here: Flowcharts to help selecting the proper analysis technique and test
Unfortunately I could not find implementations of such flowcharts. By implementation of the flowchart I mean the program could ask you some questions, and based on your answers would run some test. Do you know if such programs exist? (it would be better in R but implementations in other programming languages are also welcome)
Thanks a lot!
 A: There is no implementations because the flowcharts describe simple heuristics, while real life cases are much more complicated than this. The flowcharts described by you are connected to, often criticized, "cookbook" approach to statistics. Flowcharts are helpful for passing your applied statistics exams, but in real life may not be that helpful given the complicated nature or real-life statistical problems and datasets. Below you can find few quotes dealing with this approach.
Rasmus Bååth:

In Bayesian statistics you can quickly escape the cookbook solutions,
  once you get a hang of the basics you are free to tinker with
  distributional assumptions and functional relationships. In some way,
  classical statistics (as it is usually presented) is a bit like
  Playmobile, everything is ready out of the box but if the box
  contained a house there is no way you’re going to turn that into a
  pirate ship. Bayesian statistics is more like Lego, once you learn how
  to stick the blocks together the sky is the limit. (http://www.sumsar.net/blog/2014/01/bayesian-first-aid/)

Herbert Spirer and Louise Spirer:

Most textbooks offer "cookbook" approach of analysis of data without
  advising the reader what will happen to the recipe if one of the
  ingredients is left out... (Misused Statistics, p. 6)

Michael R. Hulsizer and Linda M. Woolf:

A cookbook approach to teaching of statistics may make the material
  more accessible to students. (...) Students need to decide what to
  bake (what to study), collect the ingredients (data collection),
  prepare the dish (data analysis), finish preparing the dish (data
  analysis), finish preparing the dish (interpretation of results), and
  present the food to one's guests (publication/preparation). (...)
  However, this strategy believes that fact in statistics, data are not
  always neat or precise and researchers can use more than one procedure
  to explore a problem. (A Guide to Teaching Statistics., p. 71)

The quotes are quite random, but should give you some overview of the critique.
The same with flowcharts, they may be helpful with simple, "textbook" problems, but may easily fail in more complicated situations. Furthermore, real-life usage of such flowcharts needs its user to make number of subjective decision, e.g. on critical value of $p$-value, or assessing if sample is "normal" enough etc. so they cannot be applied automatically.
