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Will R have more glitches on one operating system as opposed to another, or is it pretty much the same? robert

...ot;. It's not an outlier. > > The more R gravitates toward "black box" functions, the more some > users are encouraged to let them do the work.You pays your money and > you takes your chances. > > Jim > > > On Thu, Nov 30, 2017 at 3:37 AM, Robert Wilkins <iwritecode2 at gmail.com> wrote: >> R has a very wide audience, clinical research, astronomy, psychology, and >> so on and so on. >> I would consider data analysis work to be three stages: data preparation, >> statistical analysis, and producing the report. >> This regards the...

...;) has been recorded as a metric value". It's not an outlier. The more R gravitates toward "black box" functions, the more some users are encouraged to let them do the work.You pays your money and you takes your chances. Jim On Thu, Nov 30, 2017 at 3:37 AM, Robert Wilkins <iwritecode2 at gmail.com> wrote: > R has a very wide audience, clinical research, astronomy, psychology, and > so on and so on. > I would consider data analysis work to be three stages: data preparation, > statistical analysis, and producing the report. > This regards the process of getting t...

R has a very wide audience, clinical research, astronomy, psychology, and so on and so on. I would consider data analysis work to be three stages: data preparation, statistical analysis, and producing the report. This regards the process of getting the data ready for analysis and reporting, sometimes called "data cleaning" or "data munging" or "data wrangling". So as

...are of course free to trash. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Nov 29, 2017 at 8:37 AM, Robert Wilkins <iwritecode2 at gmail.com> wrote: > R has a very wide audience, clinical research, astronomy, psychology, and > so on and so on. > I would consider data analysis work to be three stages: data preparation, > statistical analysis, and producing the report. > This regards the process of getting...

...you know multiple tools and the underlying theory you are working with then you are more likely to succeed, so don't limit yourself by dismissing R for reasons of comparative popularity. -- Sent from my phone. Please excuse my brevity. On November 21, 2017 11:14:45 AM PST, Robert Wilkins <iwritecode2 at gmail.com> wrote: >How difficult is it to get a good feel for the internals of R, if you >want >to learn the general code base, but also the CPU intensive stuff ( much >of >it in C or Fortran?) and the ways in which the general code and the CPU >intensive stuff is connected...

How difficult is it to get a good feel for the internals of R, if you want to learn the general code base, but also the CPU intensive stuff ( much of it in C or Fortran?) and the ways in which the general code and the CPU intensive stuff is connected together? R has a very large audience, but my understanding is that only a small group have a good understanding of the internals (and some of those

what does R have to compare with , say , proc surveymeans, estimate survey means/proportions with standard errors, using Taylor methods? [[alternative HTML version deleted]]

...> The more R gravitates toward "black box" functions, the more some > > users are encouraged to let them do the work.You pays your money and > > you takes your chances. > > > > Jim > > > > > > On Thu, Nov 30, 2017 at 3:37 AM, Robert Wilkins <iwritecode2 at gmail.com> > wrote: > >> R has a very wide audience, clinical research, astronomy, psychology, > and > >> so on and so on. > >> I would consider data analysis work to be three stages: data > preparation, > >> statistical analysis, and producing the...

...oward "black box" functions, the more some >> > users are encouraged to let them do the work.You pays your money and >> > you takes your chances. >> > >> > Jim >> > >> > >> > On Thu, Nov 30, 2017 at 3:37 AM, Robert Wilkins <iwritecode2 at gmail.com> >> wrote: >> >> R has a very wide audience, clinical research, astronomy, psychology, >> and >> >> so on and so on. >> >> I would consider data analysis work to be three stages: data >> preparation, >> >> statistical...

A procedure that , after adjusting for sampling weights, also explicitly does an age adjustment to conform with an age distribution of an older census?

Is anybody using R to do analysis of clinical trial datasets that have been put in the public domain (which are super hard to find). Not only a single data table, but the actual database, with a handful of data tables with one-to-one or many-to-one relationships? [ For example, "Adverse Events" and "Patient Info" are two datasets with a many-to-one relationship, the