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RStudio IDE System Recommendations

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While we typically shy away from providing specific recommendations for running the RStudio IDE, here is some information which could help you figure out what you need to run R and RStudio.
 
RStudio itself doesn't require a lot of computational power, so your requirements are going to be dependent on how you're using R. The number of cores, speed of the cores and the amount of RAM that you need is highly dependent on the work/analysis you will be doing. R itself is single threaded, and as such, you won't benefit from additional cores unless you are familiar with the various libraries that parallelize work and are then able to leverage multiple cores. If you are new to R and data analysis, it is unlikely that you would use more than 1 of your cores and more than 1 GB of RAM for most of your analyses.  However, if you intend to be analyzing larger data sets (>1GB) then it would be wise to invest in more RAM.  Generally speaking, most people don't leverage the parallelization in R, and so you are better off with fewer cores that are faster than more cores that are slower.
 
For any further questions about system recommendations for R, we advise that you check out the resources available here.

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