- #DOWNLOAD R MARKDOWN FOR MAC HOW TO#
- #DOWNLOAD R MARKDOWN FOR MAC MANUAL#
- #DOWNLOAD R MARKDOWN FOR MAC FULL#
- #DOWNLOAD R MARKDOWN FOR MAC SOFTWARE#
#DOWNLOAD R MARKDOWN FOR MAC MANUAL#
This is not a manual and it does not replace the reference work out there it just complements it with my experience.
#DOWNLOAD R MARKDOWN FOR MAC HOW TO#
I will start by explaining why I prefer R markdown over MS Word or \(\LaTeX\), and then follow with some tips on how to start and get used to it.
If you are still exploring or already leaning on the building-blocks, more-typing, interoperability-loving side, keep reading.
If you lean towards the first side, to pre-packaged, user-friendly, everything-in-buttons kind of software, then this post is probably not for you. It is not always a conscious choice -it depends on what you learn and how– but I believe that at some point it should be. Using either R (or Python) to do analyses or using, instead, SPSS, Excel or even JASP 4, is standing more towards one side of the continuum or the other. In my case, I like to go to the second side, because I like learning to use all the little tools and combining them in all my freedom, rather than bumping against the walls of a beautiful, user-friendly marble salon. I see them as poles in a continuum, and we may move between one or the other as we get more familiar with different tools. I put R Markdown and the family of packages that expands its functionality on that side 3. It also implies interoperability: the programs must communicate with each other, and therefore work with the same file formats. That is how the command line programs in Linux work, for example.
#DOWNLOAD R MARKDOWN FOR MAC FULL#
On the other side you have tons of tiny programs, each of them fulfilling one unique function, offering you the full freedom to combine them as you wish, but no guiding path, no set workflows that can help the initiate.
#DOWNLOAD R MARKDOWN FOR MAC SOFTWARE#
(I also tend to link this to proprietary software with their own particular file formats that almost no other software can read.) I would put MS Word on that side. On the one hand you have programs that bundle a lot of functions into a very neat, user-friendly interface, and select the workflows and functions that you’re more likely to use -but then limit you to the options they give you, and there is not much more you can do. My father once drew this mind-blowing comparison to me that I keep applying to a lot of tech-related things and to people’s attitude towards software 2. It also depends on how you approach technology and research.
Like with any other new skill, whether you can take on this challenge depends on how much time and energy you have, on the support you already receive to learn new skills, on the community around you and what tools they use. Artwork by you have never used R Markdown, and especially if you have no familiarity with R at all, I hope you to still give it a try, even if it seems very intimidating at the beginning. Once the interest is sparked, in the following post I will share my experience writing my PhD thesis with R Markdown. In this post I hope to convince you to use R Markdown -at least plant a seed that will eventually grow into a burning desire to use it. Here I want to talk about R Markdown, which is quite close to \(\LaTeX\) in many respects and entirely different from Word, although you can still make your Word-demanding publishers happy with the help of packages like officedown ( Gohel and Ross 2021). In certain fields \(\LaTeX\) is also very popular. As a researcher with (maybe quantitative) data, what do you use to write, and did you ever think of alternatives? A very common answer to the first question is MS Word, because it’s a popular program that comes with the very popular OS Windows, everyone knows how to use it (it is indeed quite user-friendly) and publishers will often ask you for Word files 1.
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