I would say the best way to learn statistics and R is to have various research topics in mind that interest you and as you are studying the various topics in statistics and commands in R think about how you would use them to aid you in addressing the topics of interest.

With R in particular, the key is practice, reading is fine but without getting down and dirty with the syntax your progress will be limited. It is helpful to use the question mark command (i.e., ?histogram) in R as you most likely know brings you to their page addressing the commands and functions. There is usually sample code there in which you can directly copy and paste into your own program and tinker with. If you are feeling overwhelmed with this program just give it time. When I first started using R, it seemed like the most daunting task. Now, there is still an enormous amount of things I don't know about but, I have no problem figuring them out and using the program to create figures is pretty much second nature (just make sure to have skeletal prototypes for the various figure types and this will become even easier). 

As for statistics, just try to understand what you are attempting to do with the various tests and always brush up on the basic tenants of the science: knowing what a p-value means, actually reporting effect sizes instead of just p-values, the importance of distributions and their relationship to one another (i.e., how this relationship connects them into a single family that allows for predictions to be made using generalized linear models despite seemingly extreme dependent variable differences. Also, everything is essentially regression, ANOVA, ANCOVA, MANOVA, etc. these are just particular circumstances of regression. If you can see their connection with regression as well as be familiar with the other mentioned topics... I would say, damn! this is a person who knows statistics.

Practice, practice, practice, my friend and I wish you all the best,

Logan Netzer

Hi, 

I guess that the best way to learn statistics and R is by reading the following book:

Analyzing Linguistic Data: A Practical Introduction to Statistics using R

R. H. Baayen

Cambridge University Press, 6  2008

I would say the best way to learn statistics and R is to have various research topics in mind that interest you and as you are studying the various topics in statistics and commands in R think about how you would use them to aid you in addressing the topics of interest.

With R in particular, the key is practice, reading is fine but without getting down and dirty with the syntax your progress will be limited. It is helpful to use the question mark command (i.e., ?histogram) in R as you most likely know brings you to their page addressing the commands and functions. There is usually sample code there in which you can directly copy and paste into your own program and tinker with. If you are feeling overwhelmed with this program just give it time. When I first started using R, it seemed like the most daunting task. Now, there is still an enormous amount of things I don't know about but, I have no problem figuring them out and using the program to create figures is pretty much second nature (just make sure to have skeletal prototypes for the various figure types and this will become even easier). 

As for statistics, just try to understand what you are attempting to do with the various tests and always brush up on the basic tenants of the science: knowing what a p-value means, actually reporting effect sizes instead of just p-values, the importance of distributions and their relationship to one another (i.e., how this relationship connects them into a single family that allows for predictions to be made using generalized linear models despite seemingly extreme dependent variable differences. Also, everything is essentially regression, ANOVA, ANCOVA, MANOVA, etc. these are just particular circumstances of regression. If you can see their connection with regression as well as be familiar with the other mentioned topics... I would say, damn! this is a person who knows statistics.

Practice, practice, practice, my friend and I wish you all the best,

Logan Netzer

Nowadays there are so many different books and courses on R that we should be able to recommend one suitable to your research interests if you tell a bit more about what you want to use R for. I agree with Logan Netzer's answer above. I would add that you should try to get somehow familiar with R as a language before you attempt to use it for statistics, If you want to learn R through exploration, then you may want to have a look at a book I am writing, you can get it for free at http:/leanpub.com/learnr. It is still work in progress. Roger Peng's books available at leanpub.com are excellent and follow a more tradiational approach and are already complete.

As for statistics, I like very much the book "Statistics and Scientific Method: An Introduction for Students and Researchers" by Diggle and Chetwynd (ISBN: 9780199543199). As Logan Netzer says, try to learn the generalities rather than each instance as a special case. And yes, practice, practice, and revisit the same data many times along the way... and before jumping into tests, explore the data from as many angles as possible: let the data speak.  And keep in mind that statistics is not an exact science, and there is very rarely a single "correct" way of analysing a data set.

https://leanpub.com/rprogramming

https://leanpub.com/learnr

Hi Krishna,

Others in this thread have offered good resources for R and data analysis; however, there are plenty of free alternatives available to help you. 

First, if you haven't already, I highly suggest downloading R-Studio (https://www.rstudio.com/products/RStudio/) to make R both easier to use and more appealing to work in. It includes a code editor, debugger, and visualization tools, and is available for free! The majority of tutorials or resources you see will use R-Studio.

Second, I would suggest following along with tutorial videos or a textbook to get a basic overview of R, both in terms of how to use the environment as well as how to use it for statistical analysis. The best free, online resource I've found through the years is DataCamp (https://www.datacamp.com). They have free tutorials that start you off with the very basics of R and statistics, allowing you to work your way up comfortably. It covers topics like getting started in R, assigning variable names, data types, etc., and moves up to things like writing functions, creating 'for' loops, and graphing your data. I can't recommend it enough. 

As a side note, DataCamp also has a stellar website called R Documentation (http://www.rdocumentation.org) which allows you to search R Packages (downloading and installing reusable functions that allow you to do countless things in R). This will come in handy as you become more comfortable with R.

Third, I would work through a textbook with real examples and explanations. Dr. Daniel Navarro of the University of Adelaide has a free textbook "Learning Statistics with R" (http://www.fon.hum.uva.nl/paul/lot2015/Navarro2014.pdf) available on his website. While it's geared towards Psychology and the Social Sciences, it will provide you with a basic introduction to R, how to import data and write functions, and provides plenty of examples, all while covering important aspects of statistics.

From there, it's all about using R as much as possible - practice, practice, practice! It will feel slow and frustrating at first, but once you get the hang of R, it will become fun and allow you to do whatever you could ever want.

Good luck, and keep at it! 

https://www.rstudio.com/products/RStudio/

https://www.datacamp.com

http://www.fon.hum.uva.nl/paul/lot2015/Navarro2014.pdf

http://www.rdocumentation.org

Waoh!  All the suggestions given to you are enough to get you started. All the best 

Waoh!  All the suggestions given to you are enough to get you started. All the best 

Dear Krishna,

absolutely excellent answers so far.

When I started to teach myself R, after going through the usual R studio setup I worked through "R for dummies" by Andrie de Vries and Joris Meys. Still is a quick and easy reference as I am not using R on a regular basis but with weeks to months in between.

http://rfordummies.com/

I also enrolled myself in an online course, a MOOC, by Microsoft together with edX. I found this one extremely good. I am working full time as a clinician. The course allowed me self paced studying over a four week period, with regular coding practice, and tests. You can do the course for free, or if you want to pay the $49 enrolment fee, you will after succesful completion be able to download a certificate as well.

https://www.edx.org/course/introduction-r-data-science-microsoft-dat204x-1#!

https://www.edx.org/course/programming-r-data-science-microsoft-dat209x-1

John Hopkins University runs an online specialisation on data science and R programming on coursera. These are excellent  - I only did a couple of modules, though, which was sufficient for my needs. There are several MOOCS bundled together, which you can complete with a capstone project at the end. 

https://www.coursera.org/specializations/jhu-data-science

Good luck with your endeavour and best wishes,

Immo

Also one should mention that there are different levels of R-use. My own experience for statistical analysis is that if your data is well organized the statistical analysis can be done with a few lines and rudimental knowledge of R. (usually import the data (1 line) do the analysis 2 lines and see the results).

If you use R to organize your data (for example you combine different datasets) or you use R to draw graphs... or you do more complicated analysis often a deeper knowledge of R is requires as it is for non standard models etc.