An argument for why careful coding in R is better than an Excel spreadsheet

I spend a fair amount of energy encouraging my coworkers to use R because you can write reusable code that means checking for errors is simple and you can re-run it on different data sets without having to manually copy and paste all your data and fix up any indexing if it’s the wrong length.

There’s been a bit of buzz recently about how two economists really dropped the ball when they published a paper showing that high levels of national debt as a percentage of GDP slows economic growth. I won’t write any more about it because it’s been done by better writers and statisticians, but I’d like to bring your attention to the following articles:

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3 thoughts on “An argument for why careful coding in R is better than an Excel spreadsheet

  1. blenz3

    The problem is that few professionals outside of IT/software dev really understand programming well enough to use R. I have been encouraging coworkers and friends to learn VBA so that they can stay within the comfort of their Excel environment and generalize their analyses, but even this has been impractical. I like R, but I just think the complexity is too great for the majority of non-programmers.

    Reply
    1. Sam Clifford Post author

      I’m tutoring in a new first year quantitative methods class. We’re teaching a bunch of 17-18 year olds, most of whom have zero background in programming, how to use R. I don’t expect that at the end of the semester they’ll all be proficient at using R to do all of their data analysis but by showing them that they can operate on entire columns with functions rather than by click-dragging a formula from a cell I’d hope that we can convince them that R makes certain things easier.

      Reply
      1. blenz3

        I’d be interested to see how that turns out! Most of my past and present coworkers have been barely able to use the f(x) bar in Excel let alone understand the basics of an R program or interactive session. Is the class more focused on the programming aspects or will the emphasis be on working with the R shell to run the analyses?

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