Here is an interview with Rob Kabacoff, Ph.D, author and creator of the popular R reference website Quick-R (http://www.statmethods.net/)
Ajay- What are the reasons you started using R?
Rob- I had been using SAS and SPSS for many years, when I applied for a position that required a solid command of R programming. I had some experience using S in the early days and wanted to refresh my knowledge before the interview. I was very surprised to see how the language and platform had grown, and how powerful and comprehensive it had become in its new incarnation. It quickly became apparent that I would not be able to develop any kind of expertise in time for the interview. However, despite turning down the position, I become smitten with the language, and continue to use and study it to this day.
Ajay- What were your motivations in writing Quick R and designing your website
Rob- Although I was an experienced programmer and statistician, I found R a very difficult language to learn. The number of packages and functions available can feel overwhelming, and it can be hard to get handle on the language as a whole. I learn best by teaching, so I created Quick-R as a place where people who were familiar with statistics, but not R, could jump into the language rapidly. It started out as a simple cookbook and has expanded ever since.
Ajay- What has been the feedback to your website so far
Rob- The feedback has been amazing. I have received roughly 500 emails thanking me for the site, and there are 10,000+ unique visitors a day. A couple of years ago Manning Publishing asked me to write a book about R and Quick-R turned in “R in Action: Data Analysis and Graphics with R”. After only one year I am already writing a second edition (R changes fast!), but I still support Quick-R every day. Knowing how much it is used is incredibly gratifying.
Ajay- Name some consulting projects in which you used R for great effect? ( or real time case studies with confidential details suppressed)
Rob– I do a lot of research on global leadership. The goal is to understand how leaders in different countries approach the leadership role, what behaviors they rely on, what behaviors they expect from others, and what values they bring to the table.
Differences among leaders in different cultures can be enormous – and understanding them can reduce misunderstandings, conflicts, and tensions. Such research frequently entails comparing the leadership behaviors of business executives and government officials in dozens of countries on dozens (or hundreds) of variables. It can be very challenging to understand such complicated observational data, and communicate it a meaningful way to a nontechnical audience. R really excels at both model building and graphics. In particular, I rely on packages like relimpo to help identify the relative importance of variables in predicting leadership effectiveness, and graphics packages like ggplot2 to build plots that convey the results in easily digestible ways.
Ajay- Initiatives like coursera, and multiple free video lectures on the internet, and helpful websites like yours are helping introduce R to a broader than just a niche audience. How can we make learning statistics and tools more popular.
Rob- I love statistics, and actually think that it is becoming increasingly popular on its own. With the advent of big data, fast and powerful software, and the internet as a driving force, the field of statistics is finally becoming sexy. I am amazed at the number of jobs I see for data scientists of all types (analysts, programmers, modelers, data miners) listed in popular websites like Monster and Career Builder. I think that quantitatively oriented students will always gravitate to languages like R if there are practical books, videos, and websites that show real world applications. Once you see how something can be used, I think you are more willing to buckle down and learn the nitty-gritty details necessary to make it work. For people averse to programming, I think that easy to use GUIs become increasingly important. This is why IBM SPSS has done so well. RCommander and Deducer are good examples of GUIs that can help you to incorporate R into courses that do not include programming.
Ajay- How can we make statistics books more affordable to students while adequately compensating authors, including usage of web based tools.
Rob- Boy, that is a tough one. Quick-R is obviously free and I donate the time and expense it takes to keep it running because I want to contribute to the community. Writing is much harder than I ever imagined and the hundreds of hours it took to write R in Action were exhausting and painful. Even if I didn’t get royalties, I probably would still have written it, but I might not be doing a second edition now. To be honest, only a small portion of the income from traditionally published books go to authors. The rest goes to the publisher, and I can’t speak to costs or profit. To bring the cost down, we would have to reduce the cost to publishers, their profits, or find an alternative distribution model. One solution may be to have authors publish small texts (booklets) that are less time consuming to write and can be offered in PDF format for free or for a small fee. These can be practical use books, explanations for frequently misunderstood topics, or solutions to particular problems. Additionally, I have found that authors will frequently work for recognition (won’t we all?), as well as money. Rewarding authors with attention, opportunities to speak, teach, etc., may be very motivating for many such individuals. Perhaps we could create and promote more websites that aggregate donated online textbooks – giving aspiring authors an opportunity and an outlet for their writing, and an audience in the process.
Rob is a statistical consultant and research methodologist for more than 25 years. His Ph.D. was originally in psychology.For the past 15 years he have been head of research for Management Research Group, a global HR development firm in Portland, Maine and Dublin, Ireland
Rob primarily study cross-cultural leadership and issues of workplace diversity. Before that, Kabacoff was a graduate school professor in Southern Florida for 10 years teaching multivariate statistics and statistical programming (and surprising, family therapy and adult psychopathology).
The book inspired by the Quick -R website is now available! It takes the material there and significantly expands upon it. If you are interested, you can get it here. Use promo code ria38 for a 38% discount
R in Action
Data Analysis and Graphics with R
Robert I. Kabacoff
August, 2011 | 472 pages
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