Reddit mentions of Getting Started with R: An Introduction for Biologists

I've posted a similar answer before, but can't find the comment anymore.

If you are interested in doing your own statistics and modeling (like regression modeling), learn R. It pays amazing dividends for anyone who does any sort of data analysis, even basic biostats. Excel is for accountants and is terrible for biological data. It screws up your datasets when you open them, has no version control/tracking, has only rudimentary visualization capabilities, and cannot do the kind of stats you need to use the most (like right-censored data for Cox proportional hazards models or Kaplan-Meier curves). I've used SAS, Stata, SPSS, Excel, and a whole bunch of other junk in various classes and various projects over the years, and now use only R, Python, and Unix/Shell with nearly all the statistical work being in R. I'm definitely a biased recommender, because what started off as just a way to make a quick survival curve that I couldn't do in Excel as a medical student led me down a rabbit hole and now my whole career is based on data analysis. That said, my entire fellowship cohort now at least dabbles in R for making figures and doing basic statistics, so it's not just me.

R is free, has an amazing online community, and is in heavy use by biostatisticians. The biggest downsides are

• R is actually a strange and unpopular general programming language (Python is far superior for writing actual programs)
  
• It has a steep initial learning curve (though once you get the basics it is very easy to learn advanced techniques).
  
  Unfortunately learning R won't teach you actual statistics.... for that I've had the best luck with brick-and-mortar classes throughout med school and later fellowship but many, many MOOCs, textbooks, and online workshops exist to teach you the basics.
  
  If I were doing it all over again from the start, I would take a course or use a textbook that integrated R from the very beginning such as this.
  
  Some other great statistical textbooks:
  
  
• Introduction to Statistical Learning -- free legal PDF here -- I can't recommend this book enough
  
• Elements of Statistical Learning -- A masterpiece of machine learning and modeling. I can't pretend to understand this whole book, but it is a frequent reference and aspirational read.
  
  Online classes:
  So many to choose from, but I am partial to DataCamp
  
  Want to get started?
  
  
• Download R directly from its host, CRAN
  
• Download RStudio (an integrated development environment for R that makes life infinitely easier) from its website (also free)
  
• Fire up RStudio and type the following commands after the > prompt in the console:
  
  install.packages("swirl")

library("swirl")

swirl()
  
  And you'll be off an running in a built-in tutorial that starts with the basics (how do I add two numbers) and ends (last I checked) with linear regression models.
  
  ALL OF THAT SAID ------
  
  You don't need to do any of that to be a good doctor, or even a good researcher. All academic institutions have dedicated statisticians (I still work with them all the time -- I know enough to know I don't really know what I am doing). If you can do your own data analysis though, you can work much faster and do many more interesting things than if you have to pay by the hour for someone to make basic figures for you.

Someone over on r/rlanguage posted this link to a list of R help resources. As we don't know quite what level you're at, you may want to look through there to see what's applicable to you.
If you are a total novice, one site I've had recommended (and is also linked on the above blog) is datacamp. Personally I found this useful as a start to learning some of R's commands, but the first chunk of the course left me unable to actually make or run a program as it didn't fill in the basics (eg what a working directory is, how to actually download R). So I used that website in conjunction with the book getting started with R - whilst it is targeted at biologists, the first half is certainly applicable to anyone getting to grips with R.
You'll have to decide yourself whether it's worth spending money on books if you'll only be using them for this one class or whether it would be better trying out some of the free online resources (or seeing if you find free ebook versions!).
As u/fang_xianfu said, a specific question will probably give you more targeted help and advice, so ask away!