What is How to in R?
How to in R is dedicated to expanding the use of R to all reaches of industry and academia. R presents a steep learning curve, and just the thought of a programming language can cause some to run for hills (or the presumed safety of Excel). But I have seen first hand, if someone can learn Excel, they can learn R. This site is committed to breaking down some common R hurdles in a simple and easy to understand format. The truth is, even the most experienced R user has multiple references that guide them through R analyses. How to in R is starting off simple, providing reference material to get people up and running. But the hope is that user feedback drives the content on How to in R. It will grow and continue to build it's reference library based on user requests.
The R community is extremely active and vibrant and I am excited for the opportunity to open it's doors to even more.
Why choose R?
With all the data analysis and statistics packages out there today, it is common to ask why one should take the time to learn R? I'm not going to claim that R is superior to all other software packages out there, in fact it's probably not. Choosing the right statistics package is dependent on a number of factors and ultimately most packages will get the job done. That being said, there are a few key reasons to consider R for your analysis needs:
R is free: R is an open-source project built by the R foundation for Statistical Analysis. It is completely free of charge, no download costs or license fees. You can install R on an unlimited number of systems.
R can standardize your analysis process: With R being an unlimited free package, you can easily install R on all your systems. This includes your personal (home) and professional (work) systems. Also, you are no longer restricted to the licenses held by your corporation. Move to a new company that does not carry your go-to software license? Not a problem with R!
Unparalleled Compatibility: Given that R is open-source, contributors have built add-ins making R compatibility with just about every standard available. This compatibility gives R an unparalleled flexibility to be used in all functions.
You have a question, we have the answer: R has led to the development of a massive community of users ready to help at a moments notice. If you have a task that can be benefited from R, it has probably already been documented somewhere, and if not, contributors also welcome a challenge and are willing to help.
R is quickly being accepted by academic and commercial communities throughout the world. Join the team!
How to in R is dedicated to expanding the use of R to all reaches of industry and academia. R presents a steep learning curve, and just the thought of a programming language can cause some to run for hills (or the presumed safety of Excel). But I have seen first hand, if someone can learn Excel, they can learn R. This site is committed to breaking down some common R hurdles in a simple and easy to understand format. The truth is, even the most experienced R user has multiple references that guide them through R analyses. How to in R is starting off simple, providing reference material to get people up and running. But the hope is that user feedback drives the content on How to in R. It will grow and continue to build it's reference library based on user requests.
The R community is extremely active and vibrant and I am excited for the opportunity to open it's doors to even more.
Why choose R?
With all the data analysis and statistics packages out there today, it is common to ask why one should take the time to learn R? I'm not going to claim that R is superior to all other software packages out there, in fact it's probably not. Choosing the right statistics package is dependent on a number of factors and ultimately most packages will get the job done. That being said, there are a few key reasons to consider R for your analysis needs:
R is free: R is an open-source project built by the R foundation for Statistical Analysis. It is completely free of charge, no download costs or license fees. You can install R on an unlimited number of systems.
R can standardize your analysis process: With R being an unlimited free package, you can easily install R on all your systems. This includes your personal (home) and professional (work) systems. Also, you are no longer restricted to the licenses held by your corporation. Move to a new company that does not carry your go-to software license? Not a problem with R!
Unparalleled Compatibility: Given that R is open-source, contributors have built add-ins making R compatibility with just about every standard available. This compatibility gives R an unparalleled flexibility to be used in all functions.
You have a question, we have the answer: R has led to the development of a massive community of users ready to help at a moments notice. If you have a task that can be benefited from R, it has probably already been documented somewhere, and if not, contributors also welcome a challenge and are willing to help.
R is quickly being accepted by academic and commercial communities throughout the world. Join the team!
