What student is going to spend hours becoming an expert in using Stata if, when the come to do their project towards the end of the course, they cannot read the data because of an arbitrary limit on the number of Stata variables? R, on the other-hand, is only limited by the size of your computer. Take the simple issue of the size of the dataset. In all of these areas, R is ahead of Stata.
Here are a few obvious trends: much larger datasets, the growth in the use of Bayesian statistics, the increased use of other computer intensive methods of analysis, data mining, dynamic computer graphics, automatic report writing, websites for accessing databases and websites for presenting the results of statistical analyses.
Like everything associated with computing, statistics has changed enormously in recent years and I am sure that the pace of change will only increase.
#Use stata 13 software
As important as the fact that R is free, is the way that R works with the family of other free software available on the web, such as latex and knitr, and the way that so much free support can be accessed via the internet. However, Stata is reasonably priced and I do not see this as the main reason why R will win out. Obviously, R is free and this will always be a big plus, especially for students. In my opinion, Stata continues to win over R in terms of ease of use and in the way that it presents results, but RStudio has helped R to catch up and R has some important advantages of its own. Perhaps, the strong control coming from StataCorp is a weakness as well as a strength. In many ways I regret this but Stata is showing signs of being rather slow to adapt. Time will tell, but I have a feeling that left to choose between Stata and R, most students are going to choose R. This year we have made another major change, Stata and R will be taught as the main software for the masters course and SAS will become the option. I got my way and we switched to teaching both SAS and Stata, but it was immediately evident that given the choice, almost all of the students preferred to work with Stata.Ībout 5 or 10 years ago we introduced an optional, intensive short course in R for students interested in working in areas where R is the package of choice, such as genetic research. At the time, most of the analysis on the course was done using SAS. When I returned to Leicester after the sabbatical, I pressed very strongly for us to adopt Stata on our masters course in medical statistics. using Stata really does help students to learn about statistics.it is well-controlled by StataCorp so that one can have real faith in Stata’s results.it is supported by a wide range of introductory textbooks.it offers a wide range of statistical analyses.I was amazed at how quickly the students took to Stata and it was clear that Stata has a lot of advantages:
At that time, I had never used Stata, so obviously I had to give myself a crash course before I started. Alongside the lectures on statistics, the students were to get a course in using Stata. When I was there, they asked me to teach a statistics course to a group of medics and researchers. This week I would like to discuss the relative merits of the two packages and speculate a little about the future of statistical computing software.Ībout 15 years ago I went on sabbatical to the Royal Children’s Hospital in Melbourne, where I had a fantastic time. I think that this discussion follows on naturally from my recent postings about linking Stata and R.Īs you might imagine I am quite a fan of Stata, but not one who is blinded to its limitations and for a growing number of tasks I find myself turning to R. No Bayesian analysis this week, instead I want to talk more generally about statistical computing.