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Try R — A new online course, for free

• Homunculiheaded 14y ago
  For anyone interest in R without a background in statistics: I would highly recommend learning the two in parallel (if not statistics first). R is first and foremost a language for statistical computing. You really aren't going get much out of it without working on some interesting data/stats problems. Plus for most hacker types I think being able to play with the statistics you're learning about with R can be a great learning aid. However not only is it beneficial to learn stats with R, it is imho dangerous to learn R without some stats. There's already too much research being published with were 'p-value' means "the thing that t.test() output that I was told needs to be in the paper". Because R lets you play so freely with stats I find it a great tool to gain greater intuition about certain mathematical principles, but there is a temptation to let the tool do the work and the thinking for you.
  • seanlinehan 14y ago
    This is a very, very good point. Though, many of the functions that R provides just won't make any sense at all if you don't have an intuition for the statistics behind it. I have found myself reading the papers published about specific functions in order to understand the results. Do you have any resources that you suggest for beginners in statistics looking to learn on their own?
    • kayge 14y ago
      You probably can't go wrong with the Introduction to Statistics class from Udacity http://www.udacity.com/overview/Course/st101/CourseRev/1 http://www.udacity.com/overview/Course/st101/CourseRev/1
      • magicarp 14y ago
        I'm taking this right now. Can somebody provide some perspective on how thoroughly the course prepares you for using R? Does it give you a good enough grounding in statistics so that you won't shoot yourself in the foot with R?
      • BasilAwad 14y ago
        After that you can take the AI course on Udacity.
      • gwern 14y ago
        I thought http://oli.cmu.edu/courses/free-open/statistics-course-details/ http://oli.cmu.edu/courses/free-open/statistics-course-detai... was a great introduction, after completing it.
      • pathy 14y ago
        Thanks for the link, I have been meaning to revise some statistics, four years of barely doing any makes you forget a lot.
    • Homunculiheaded 14y ago
      Here's the resources I've used and found helpful (plus notes) for getting a least a basic grounding in statistics. Khan Academy + "Head First Statistics" -No matter what direction you want to go with your learning and before you start getting into street fights over Bayesian vs Frequentists philosophies, "stats 101" is the common base of 'statistics' for: Physicists, Engineers, Sociologists, Doctors, Economists, Journalists and more. Yes there are many "truths" in 'stats 101' that can be questioned, but this is the common language you'll want talking to any of these people. "What is a p-value anyway?" -A very quick, non-math heavy read on avoiding magical thinking in classical statistics. "Data Analysis with Open Source Tools" -I really love this book because it steps way out of "stats 101" land and gives a lot of really great real world advice and touches on many mathematical tools that can help you understand data. The chapter "What you really need to know about classical statistics" gives a refreshing overview of all the basic stats you've covered and explains many things that seem strange. Also the bibliography/recommended reading list from this book is fantastic. The biggest thing I've noticed as I've learned more is that statistics is a gigantic field, and can mean extremely different things depending on what field you're in. Obviously learn the advanced statistics relevant to your interests, but when you get a chance listen to how other people think about stats, and keep learning.
    • ikram 14y ago
      Take a look at the free online course on Statistical Reasoning from CMU: http://oli.cmu.edu/courses/free-open/statistical-reasoning-course-details/ http://oli.cmu.edu/courses/free-open/statistical-reasoning-c... It includes interactive exercises with an option to do them in R.
  • iaw 14y ago
    While it is predominantly a statistics language there is also a huge wealth of data manipulation capabilities in functions like plyr, aggregate, *apply, ave, subset, etc. Just in terms of organizing data sets, ignoring any statistical analysis, R is fantastic.
    • dan_yall 14y ago
      I've found Python + Pandas much better in this regard than R. Maybe it's just me, but for grouping, indexing, and manipulating tabular data, Python syntax just makes more sense. That said, R is better for stats and matrix operations.
      • hadley 14y ago
        Are you using Pandas? If so, your comment would be ironic because pandas borrows heavily from R ;)
        • Myrmornis 14y ago
          What has pandas borrowed from R, other than a 2D data structure with heterogeneously-typed columns? I guess the data frame merge invocations are similar. (I know patsy/statsmodels are introducing R's formula syntax to python, but that's not pandas.)
          • hadley 14y ago
            The split-apply-combine framework dealing with group by tasks (http://www.jstatsoft.org/v40/i01/paper http://www.jstatsoft.org/v40/i01/paper, not that there aren't other precedents) for one. But generally, Wes has used R to figure out what people want to do, and then ported an elegant interface to python.
        • RaSoJo 14y ago
          They might have borrowed from R. Wes McKinney admits to being influenced by R especialy data frames...but it makes data analysis all the more easier when i can do everything i want within the the Python environment. pandas is proving to be a bit of a longer learning curve i must admit, but then the python environment and native Matplotlib support made life oh so much simpler. That's just me though.
  • kamaal 14y ago
    Can you advice on good resources to learn statistics?
    • aorshan 14y ago
      Udacity has a intro to statistics class that you might like.
  • chernevik 14y ago
    How about not-beginners looking to refresh / deepen their intuitions? I've recently been working with the Python toolset in this space -- pandas, numpy, matplotlib -- and run smack dab into my rusty regression analysis. In particular I need to better understand the distribution assumptions underlying the error distributions and the variances around the coefficient and intercept values. Any suggestions for some deeper study / refresher?
    • sciboy 14y ago
      Honestly, the only way to understand regression is to study something like Mccullagh & Nelders book. Anything else and you are going to have a very hard time really being useful without misinterpreting the results. There are some real subtleties to interpretation of regression coefficients, and more importantly structuring your data in such a way that you will answer the questions you want. It's not an easy book, but if you've gone through to at least third year level in statistics it's approachable and you will understand it to a deep level.
    • pseut 14y ago
      Depends on the data sets you want to work with. For straight-up linear regression, with a heavy emphasis on observational data appropriate for microeconometrics, "Introductory Econometrics: A Modern Approach" by Jeff Wooldridge is absolutely phenomenal (an old edition is fine). (This is usually assigned for advanced undergraduate econ majors or non-advanced masters students; I don't know what the equivalent would be for undergraduate stats majors). For more "intuition about working with data, especially if you're a visual person," Howard Wainer's books are wonderful; one example is "Graphic Discovery: A Trout in the Milk and Other Visual Adventures." They're non-technical, short chapters, discussions of different data sets. Bill Cleveland's "Visualizing Data" and "Elements of Graphing Data" cover the same material -- graphing data -- at a more technical level. I don't know Cleveland's books would help with the issues you asked about, but... they are amazing books and if you're interested in the subject at all I can't recommend them highly enough. I don't have any free recommendations, unfortunately.
      • creamyhorror 14y ago
• xwowsersx 14y ago
  Just started this now. It's really awesome. Only wish it was a bit faster.
• 65b 14y ago
  I got a random hang after typing hel( instead of help( also on sqrt( of a vector. Also paste works when you shouldn't be able to type.
• asdasdsdasdad 14y ago
  god loves a Try R.
• hkmurakami 14y ago
  Thanks. I was sorely disappointed yesterday when I found out that Coursera classes follow a strict schedule (and that I couldn't look at the material right then) and that I wouldn't be able to try the Data Analysis with R course on their site. I'll definitely check this out :).
  • joshz 14y ago
    Videos are available on Roger Peng's Youtube. http://www.youtube.com/user/rdpeng/videos?flow=grid&view=1 http://www.youtube.com/user/rdpeng/videos?flow=grid&view...
    • hkmurakami 14y ago
      You are my hero.
  • bulldog 14y ago
    https://class.coursera.org/compdata-2012-001/class/index https://class.coursera.org/compdata-2012-001/class/index
• zkoch 14y ago
  I really like this, but one big complaint is that the auto-scroll after completing a little task isn't correct. So each time after I "pass" a particular section, I have to manually scroll down with my trackpad.
  • patched 14y ago
    Gregg here from Code School.. we actually tried making it autoscroll down at first. It was too distracting and annoying. Scrolling down when you're ready to continue just felt more natural.
    • a_bonobo 14y ago
      I found another rare, but annoying thing - on German keyboards the "~" is hidden away on the combination "Alt Gr and +", when I try to type that into the prompt under Firefox 17.0 nothing happens. Workaround is to copy-paste. Under Chrome 23.0.1271.95 the same key-combination inserts single quotation marks, weirdly enough, same workaround.
    • bcbrown 14y ago
      As far as I can tell, it's not possible to go through the lesson using just a keyboard; a mouse is required to scroll or to change focus from the embedded interpreter back to the page itself so that the arrow keys will scroll.
    • sprobertson 14y ago
      Perhaps leave autoscroll as an option? I don't like having to type, move my hand to the mouse, scroll, move my hand to the keyboard, and repeat.
• SeanA208 14y ago
  I really appreciate this! It's easy to follow and I was looking to learn the basics of R, this seems like the simplest way.
• just_saying 14y ago
  I shouldn't have to enable JavaScript to try R.
  • scrumper 14y ago
    Umm... You could download an R environment, but that's hardly a smaller footprint than enabling JS. How else would you do it?
    • just_saying 14y ago
      Well, HTTP GET and POST still work. No one seems to mind sending and receiving data that way when they're wrapped in AJAX calls.
  • ramblerman 14y ago
    "I want to partake in all the goodness the modern internet has to offer... but only on my terms!" There was a time when NoJS plugins and the likes were valid (neccessary). These days you're crippling your browser experience more and more. Which is entirely your perogative of course, but then don't make sweeping complainst about things not working. What did you really expect? Them to run your R code server side? a) This wouldn't allow the same snappy response, you'd have constant page refreshes. b) why should they overload their servers, and come up with an inferior solution to serve some self entitled anti javascript snob.
    • just_saying 14y ago
      I want to be able to say that I assuredly KNOW what my computer is doing at all times. There was a time when JavaScript wasn't minified/obfuscated, and the libraries weren't so huge as to require expert knowledge of exactly what was happening under the hood. I think your claim, that disabling JavaScript is merely invalid snobbery, is as silly as you think my idea of "crippling my experience (and by corollary everyone else's)" is. You make the assumption that I want the world to bend to my will, but I don't. All I'm pointing out is that the rich experience doesn't degrade gracefully, to a no-script experience. It doesn't even tell you that you need JS enabled, you should just know that already. I don't mind page refreshes, and I'd put forward that the type of person browsing without scripts enabled would already notice that every other page behaves that way, when scripts are turned off. If you're going to take the time to emulate the behavior of a statistics application in JavaScript, what's it take to also ensure that users get a similar experience when not enabling scripts? If a user is STUCK with an inferior browser/experience, it's not always their fault. The point I'd like make is that the answer is generally "tough. you're SOL. go get a better computer, and figure it out. try again, from somewhere else." You make the assumption that I'm being a snob, but as part of testing out any new website, I'll explore how it reacts with no styles, no images and no scripts. You tell me I want an inferior solution, and then call me the snob? How does that work? We'll probably never see eye-to-eye on these tidbits of taste-making, but maybe I'd accept your criticism a little more willingly if you called me pedantic, a paranoiac, or a browser-Luddite. Either way, I'm not taking your contrary opinion personally, but my side of the coin deserves some representation on this site. I know my opinions about flashy user experience go against the grain, and clash with the opinions of the JavaScript clique here, but I think this kind of criticism belongs in the conversation, even if it gets shouted down. Especially for bigger, well-established learning websites like oreilly.com.
• seanlinehan 14y ago
  This is great. I've nearly completed a class at UC Berkeley which was almost entirely in R and I can say with certainty that it is a marvelous language. It is powerful, concise, and has an incredibly robust community. I've experimented with many programming languages, but I have not used one which allows you to experiment as rapidly as R. I'm currently going through the Codeschool lessons to see if there is anything that I may have missed in my class. So far so good! Edit: The most important thing that I didn't see covered in the course was RStudio. Considering that R is more of a scripting language that a programming language, I've found that RStudio is instrumental is using the language to it's full capacity. While it's certainly possible, and in some cases optimal, to use R from the command line, my experience is that the GUI features of R studio are incredibly powerful. The ability to browse data frames and have graphs show up in the context of your work has been very useful for exploring and understanding data. Otherwise, the course does a pretty decent job introducing readers to the language and it's data strcutures.
  • eternalban 14y ago
    > .. RStudio .. Looks great. Downloading it now. (Thanks for the heads-up!)
  • wasd 14y ago
    Stat 133 is great. I took it with Spector and he was phenomenal.
  • wallee 14y ago
    Revolution R is also really nice to develop in. I believe that you can get an academic version for free.
    • smegglybones 14y ago
      Revolution R is just Enterprise R. RStudio is on Github, folks. Real talk.
• keithpeter 14y ago
  Section 2.1 contains the following instruction "Try creating a vector of numbers, like this:" So I typed c(5, 9, 11) and got an error message. They meant "Type the R code to create this vector:" I shall work through the rest in a few days, nice environment.
• scrumper 14y ago
  Was keen on trying this out. Crashed on me on the variables bit on the first page; just span and span. Happens a lot with these online interpreter things.
• thedaveoflife 14y ago
  For those learning R, this site: http://www.twotorials.com/ http://www.twotorials.com/ which I found on HN several months ago is fairly helpful as well.
  • mikedmiked 14y ago
    Yes! I thought I would never find this again! Thank you so much!
  • Tactix47 14y ago
    Great link, thanks so much for sharing! Looks like a very complete introduction to working with R.
• rjsamson 14y ago
  I'm constantly impressed by the high quality content that Gregg and the rest of the Code School folks put out on a regular basis and Try R is no exception. Really excellent work! Looking forward to getting through the rest of it.
• frozenport 14y ago
  I do most of my stats work in Matlab, why should I use R?
  • zmmmmm 14y ago
    The main reason I would put forward is that it's completely free and open source. That means that all your work is transferable and usable by anybody, not just people who have the ability to use Matlab (including possibly your future self).
    • temp453463343 14y ago
      Out of curiosity, if you want open source, what's wrong with Octave or the likes?
      • zmmmmm 14y ago
        I must admit, that sounds plausible and I'm not an expert with Matlab or Octave, but I understand the compatibility is reasonable but nowhere near complete. There seem to be a pretty good number of problems discussed here: http://stackoverflow.com/questions/3534867/why-when-should-i-prefer-matlab-over-octave http://stackoverflow.com/questions/3534867/why-when-should-i... But really I just feel like (certainly in my field) the open source community around R is huge and thriving and it's a better bet than Octave in terms of that.
      • SIULHT 14y ago
        lack of toolboxes
  • jme3 14y ago
    You shouldn't, necessarily. I use R almost exclusively and I absolutely love it. But people can get a little carried away with picking and recommending the "best" language for particular task. If you feel very comfortable and skilled in Matlab, and you aren't finding that there are regular situations where Matlab can't do what you want, I wouldn't really advocate switching. Same goes for someone working primarily in Python. The biggest reason I would recommend switching away from a language you're already very comfortable in would be the availability of statistical methods that aren't present in your language of choice. Statisticians tend to work in R, so much of the cutting edge work ends up in packages on CRAN. So I wouldn't dump Matlab if you're happy with it, unless you're just looking to learn something new, out of intellectual curiosity, which is always fun.
• taeric 14y ago
  So, I've started using R for some stuff I'm doing at work. I have to say that I'm basically treating it as a non visual spreadsheet. Seems everything I've used it for so far, I could have done with excel. Am I doing it wrong?
  • iaw 14y ago
    Nope, that's one way to look at it (especially if you're sticking with data frames). The nice thing about that outlook is that you can essentially automate tasks you would normally perform on a spreadsheet.
    • taeric 14y ago
      The biggest draw to me is actually the non-visual part of it. I don't get hung up on silly visual things such as column width. Or, where to put the plots I make. Granted, this has its own downsides. But so far I'm loving it. And yes, being able to essentially save off just what I did so that I can rerun the same tasks again later on a new data set is really really nice.
  • frankc 14y ago
    Not doing it wrong, but only using a subset of R. For instance, R has powerful data manipulation ability that can get your data to use the subset of R that does what Excel does. R also has a huge library of packages that go way beyond what Excel can do, especially for statistics. Sure, you can do an ols regression in Excel, but you can you do a complicated machine learning model?
    • taeric 14y ago
      I should have been clearer. I've never been "good" at using Excel. So far, I've really only done things that I would think you could do in Excel. Might be a touch overkill, but I'm not sure. I am curious which data manipulation items you are referring to. Any good pointers? I am going through the Machine Learning for Hackers book, though. So far it has been interesting. I guess I never realized that machine learning is essentially statistics. (Or am I looking at that incorrectly, too?)
• nasir 14y ago
  I did my master thesis stat works in R. it was a pain at the begining because I was not very good with stats. so learn the stats alongside.
• stfu 14y ago
  I'm just going through this and while I love the concept, there is one criticism from me. The course is very comfortable to walk through, but it doesn't make use of the benefits of the online environment. It is just "this is how it goes, now type it" kind of teaching. I am almost done with the second session, and most likely have completely forgotten most of the content from the first. If anybody else is going to try teaching stuff in a similar way, please let me try to play/try out stuff as early as possible. Even if the exercises are completely pointless, please make them a bit harder than just exchanging an "+" for an "-". It feels so pointless having such a great learning environment and not using it to make it feel less of a brain-dump process.
  • wiradikusuma 14y ago
    Same here. And sometimes after being introduced to a concept or function, I will wonder, "hmm, what if i do this.." but the embedded REPL doesn't allow you to tinker.
• goldfeld 14y ago
  R doesn't seem to get much frontpage love on HN, or even if it does and I haven't seen, what would people suggest is the technology for statistics going forward? I really hoped it would be around Clojure (e.g. Incanter[1]) and not Python, for entirely selfish reasons. [1]: http://incanter.org/ http://incanter.org/
  • a_bonobo 14y ago
    There used to be lot of hype on HN around the new statistical language Julia, not sure how far ahead and how good that thing actually is. You can do a lot of good with scipy (especially scipy.stats), but I feel like matplotlib's plotting is still behind R.
  • saosebastiao 14y ago
    The old joke is that the reason why R is awesome is that it was created by statisticians, and the reason why R sucks is that it was created by statisticians. As an every-day user of R, I can't help but think that description is perfect. It also means that R isn't going away. It is getting more popular, and there is a ton of work on improving the runtime, which will only mitigate people's itches to move away from it. But most importantly, it has the network effects to its advantage. Even as a Clojure lover, I can't see R ever being substituted. I see more hope for the Renjin project than I see for alternatives like Pandas/SciPi/NumPy, Julia, or Incanter.
  • tokipin 14y ago
    honestly i don't know of anything that can compare to Mathematica, besides its $300 price tag
    • dagw 14y ago
      And that $300 price tag goes up to $1000 if you want a license that lets you use Mathematica in any sort of commercial or professional context (it only goes up to $500 if you only want to use it an academic setting).
• zmmmmm 14y ago
  I feel like it starts off a little bit on the wrong foot by introducing basic types as scalar variables. In reality R has no scalar variables, everything is a vector, list, and scalars are immediately coerced into a vector eg: > is.vector("a") [1] TRUE This might seem like nitpicking but it leads to a world of confusion when programmers used to languages with scalars start trying to use R that way and it took me several months of confusion and weird bugs before I finally clicked and started understanding R better.
  • hadley 14y ago
    Can you give an example where the confusion between a scalar and a length one vector is important? I'm trying to figure out how to better teach R to people familiar with other languages and understanding your stumbling blocks would be v. helpful.
    • seanlinehan 14y ago
      For a strong conceptual grasp of how the language work, I think it is fundamental that students learning R (especially those with a history in other programming languages) understand that there are no scalars in the language. The main argument that I would make for this is that nearly all R functions can operate on vectors with a length grater than one. By understanding that when you send a "scalar" to a function you are actually sending a vector, I believe it is much more conceptually clear that you can, and should, send larger vectors to functions and can receive the expected results. This is in comparison to most other programming languages where it would be necessary to iterate over a list or array in order to operate on each individual element. For example, if you told somebody familiar with, say, PHP to add 2 to each element in a vector, they would likely break out the oh-so-familiar for loop to iterate over each element and apply the transform. This is completely suboptimal in R, as you could just do vector + 2 and receive the exact same thing.
      • hadley 14y ago
        Ah, that makes sense. Thanks!
• WinnyDaPoo 14y ago
  Shucks! It won't let me type '=' in Opera! :(
  • temp453463343 14y ago
    I'm not having this problem in Opera... I'm running version 12.11
    • WinnyDaPoo 14y ago
      Yup, Opera 12.11 on Debian Testing x86_64. _ and - result in - = and + result in + This is so odd...
      • temp453463343 14y ago
        Oh, I'm on Windows... maybe a platform depended bug?
        • WinnyDaPoo 14y ago
          I'd suspect it could be. It wouldn't be a first for Opera.
• nerfhammer 14y ago
  Looks like they emulated some features of readline in their javascript shell! ^A and ^E work (but no support for ^T, ^W, ^U...)
• bernardom 14y ago
  Beautiful website. I highly recommend supplementing a course like this (where you learn about the language's ecosystem) with the R Cookbook from O'Reilly. It's been a lifesaver for me, and helped me learn R over the course of a few months of needing it at a new job. Now I find that I need to learn something else for data munging- R is terrible at data manipulation and querying. The querying bit is solvable with the incredibly useful sqldf package from Google. The package allows you to use SQL syntax to query your data.frames (by creating, populating, querying and deleting a psql table in the background). Example: I have a dataframe named dfrm with columns named "id" "height" "name" If I want the heights of all people whose names start with D, I would need to use: > dfrm$height[which(substr(dfrm$name,1,1)=='D')] Terse, but painful. Compare to: > sqldf("select height from dfrm where name = 'D%'") Much easier!
  • agentq 14y ago
    I actually find base R excellent for data munging and manipulation, even without using additional packages. Here is a reproducible example that very easily accomplishes what you were trying to do (first two lines just set up a sample data frame) set.seed(123) dfrm <- data.frame(height=runif(20), name=paste(sample(LETTERS[1:5],20,replace=TRUE),letters[1:20])) subset(dfrm, grepl('^D',name), sel=height) Basic R functions like subset, transform, with(in), reshape, aggregate, (a,ma,ta,sa,va}pply, match, grep(l), by, split, table, etc. allow you to accomplish just about any data frame munging you might want. Add on the plyr, reshape2, data.table, xts/zoo packages and you're ready to tackle just about anything. I'm not a big fan of sqldf because imo R is not supposed to act like SQL. Using sqldf in practice would require a lot of query string manipulation and takes away from the nice functional features of R. Nevertheless, it is very easy to write incomprehensible R code. The best way to avoid this is to take one of the existing style guides (Google, Hadley Wickham's) and adopt it seriously.
    • Myrmornis 14y ago
      One drawback with R is that in computations like this, several intermediate data structures with one dimension equal in length to nrow(dfrm) are allocated. Traversing an iterable of tuples is a simple way to think about it, is efficient, and ties in with other technologies e.g. relational databases. R is often people's first language (e.g. science graduates) and those people would be better off learning how to iterate over tuples than learning the obscure bestiary of data structure manipulators you point out.
• iaw 14y ago
  For those who want to go deep : http://www.burns-stat.com/pages/Tutor/R_inferno.pdf http://www.burns-stat.com/pages/Tutor/R_inferno.pdf
• id_ris 14y ago
  I've been using R extensively for the past 12 months and have achieved a high level of comfort with the language. Now I find myself at a wall because of my lack of math and statistics background. I've taken R as far as I can, or put more properly, R has taken me as far as I can go without learning more math. With that said, I have little reason to use R right now except for it's excellent plotting ability with ggplot2. Otherwise for data munging, wrangling, connecting to databases, doing unit testing, etc - R is a giant PITA. Better to stick to Python for that. And as I learn D3, I think I'll use R even less for visualization. Therefore R will only be valuable to me once I can harness it's power for data mining and machine learning, which is it's killer feature, IMHO.
  • hadley 14y ago
    Would love to hear what you find most painful about data munging/wrangling and unit testing. It's something that I've been trying to improve in R (e.g. http://vita.had.co.nz/papers/tidy-data.html http://vita.had.co.nz/papers/tidy-data.html and http://journal.r-project.org/archive/2011-1/RJournal_2011-1_Wickham.pdf http://journal.r-project.org/archive/2011-1/RJournal_2011-1_...)
    • tanyaM 14y ago
      Do you think the love it/hate it dichotomy over R for data 'munging' stems from different ways of thinking about data. I'm slowly getting comfortable in R since returning to work in a sort of freelance arrangement that makes me highly motivated to use free or affordable tools. I started out, however, in clinical epidemiology data analysis using MS Access and SAS. I still think of data in terms of rectangular data sets, RDBMS and sql. I have a hard time with vector and matrix related terminology. I think I'm going to end up using reshape2 and data.table a lot since sqldf is noticeably slower even with my small data sets (compared with web analytics, finance, etc). The problem with sqldf and variable names containing a dot is a real drag as I try to adopt good coding style. I am missing the clarity and familiarity of sql statements, though, as I try to find my new workflow in R. I hope a more unified approach to data munging emerges soon. BTW, I totally espouse the reproducible research (RR) method of documenting study design, analysis, interpretation... I am loving knitr and latex for RR so I can no longer imagine using different tools for data munging and analysis.
• sonabinu 14y ago
  A nytimes.com article on R outlining it's history and how it is moving from academia to main stream data analytics http://www.nytimes.com/2009/01/07/technology/business-computing/07program.html?pagewanted=all&_r=0 http://www.nytimes.com/2009/01/07/technology/business-comput...
• prezjordan 14y ago
  Oh man I really wish I had this at the beginning of the semester. I'm towards the end of a grueling stats course - difficult, and not the best professor. Each homework assignment I feel like I barely scrape by without really learning. This is the first time I've ever felt this way about school.
  • aggronn 14y ago
    This has been a very common theme through my undergraduate stats education.
• prashantganti 14y ago
  I am currently reading the "The Art of R programming" by Norman Matloff and it is a good book for R beginners. Some familiarity with maths and stats basic is obviously required though.
• tekniiq 14y ago
  numpy is the best!
• merlinsbrain 14y ago
  I was very interested in the course syllabus for 'Statistics One' by Prof. Andrew Conway. I missed the course on Coursera and now I'm unable to view the course archive. Does anyone know where I can find the lectures? (Yes, I've googled some.)
  • MichaelJW 14y ago
    Take a look here: http://www.universalsubtitles.org/en/teams/coursera/?project=stats1 http://www.universalsubtitles.org/en/teams/coursera/?project... Credit: http://www.aiqus.com/questions/38783/download-upcoming-coursera-videos http://www.aiqus.com/questions/38783/download-upcoming-cours... Edit: Is this like posting a pirate link?
    • merlinsbrain 14y ago
      Thanks a ton! And no I don't think so, as they claim "Amara gives individuals, communities, and larger organizations the power to overcome accessibility and language barriers for online video." You just helped me watch a course that was posted for free online. Isn't that the point of this? :)
  • tomku 14y ago
    I took that course when it was running on Coursera, and I honestly can't recommend it (in its current state, at least) to anyone looking to learn basic statistics. It covered a lot of material, but the quality and order of coverage was very inconsistent. The first couple weeks were fine, but it felt really odd to jump from correlations and scatterplots into regression, then come back to t-tests and AOV afterwards. There were also some errors in the R code on the slides, which led to a lot of confusion on the discussion forums during the class. As a student, it didn't feel like the class's pedagogical approach was very good, and I'm now finding myself using other resources to fill in the gaps. If you'd like to hear more about those other resources I'd gladly post a list, but they're mostly Python-centric. One that I can whole-heartedly recommend even if you stick with Prof. Conway's class is the set of lectures from Roger Peng's "Computing for Data Analysis" class on Coursera. The course itself isn't available at the moment, but the videos are on his Youtube channel[1]. It teaches R from a programming perspective, and you'll find the content invaluable once you start writing R code that's more complex than a couple stats functions and a plot. [1]: https://www.youtube.com/user/rdpeng/videos?flow=grid&view=1 https://www.youtube.com/user/rdpeng/videos?flow=grid&vie...
• jianmeng 14y ago
  bug report: Matrices > plank[, 4] [1] 7 8 This should be > plank[, 4] [1] 0 8 // 0 here for plank[1, 4] <- 0 http://tryr.codeschool.com/levels/3/challenges/17 http://tryr.codeschool.com/levels/3/challenges/17
• jenni18071 14y ago
  chisq.test (arbre,simulate.p.value=TRUE)
• jenni18071 14y ago
  chisq.test([14,25,1,8,25,4,7,15,23,6,0,5,26,8,6],simulate.p.value=TRUE)