R Programming v R Analysis I sometimes see job descriptions where R is posted as analytical tool while   others mention R as programming language.
What is the difference between programming in R and performing analysis in R?
UPDATE as of 10/17/2020:
lately, new elements popping in job descriptions made me realize that my old question was too vague. Now I see jobs where "programming languages (e.g.Python) are required as well as statistical packages (e.g. R)".
In many cases, the job actually requires scripts in either language.
So it may be that the difference between scripting and programming eludes some of the job posters.
I have read somewhere a while ago that - regardless of language - scripting associates with specificity while programming with generality.
In data analysis the distinction can be clear: scripting requires access to specific example of dataset structure and specified outcome while programming is more relaxed in this respect; a program is supposed to cover a wide variety of structures, eventually using the experience gathered through scripted analyses. The options for outcome follow logically.
 A: "analysis" (in the context of R users) typically means "statistical analysis" whereas "programming" (esp. for more general-purpose languages) could mean web, frontend, backend, database, visualization, networking, security etc.
You can get away with this assumption in R only because it and its programming audience are oriented to statistics and on average have a very high level of education both in general and statistical literacy in particular... but you can't get away with this (since the generalization is not true of) with most other languages: e.g. PHP, JavaScript, SQL, VBA, C#... even MATLAB/Octave users will tend to be knowledgeable about linear algebra and probably vector calculus, but not necessarily of statistics (beyond basics like "what is standard deviation? normal distribution?").
A: R is both, its a statistical tool but there is no drop and click interface you have to use the R programming language to perform the analysis you want to do. I would assume performing analysis in R and R programming are synonymous unless the context states otherwise: for example, if someone wants a R package built they are looking for someone who can program in R rather than an analyst per se.
A: There really is not much of a difference. Or it is a difference that does not matter much.
One could say that programming is writing a set of steps to do some process, while analysis is actually doing the process. So strictly, you could say you are programming R when you design a function or procedure that can be used on many data sets, while analysis would be using such functions on a given data set.
That said, the boundary is not hard and trying to make it hard is generally not useful. I suspect that most people saying stuff like this are really trying to draw a distinction between using a language to analyze data (like in R) or using a graphical user interface that just lists all of the options for any analysis. For better and for worse, both of these are ways of analyzing data, although only the former (coding) is really useful for building new procedures for general use.
