To take a spreadsheet beyond what it's designed for — data presentation, summarization and simple calculations — into the world of complex data analysis can be an alluring prospect. But it can also be dangerous: consider these examples of spreadsheet errors that led to monumental financial losses, mistaken government policies, and even the wrong drugs being given to cancer patients.

The answer is to move your analysis into a computing environment specifically designed for data analysis: R. Burns Statistics provides a step by step tutorial on transitioning from spreadsheets to R: if you care about the accuracy if your analysis, or even just being able to reproduce your results again in the future, you should check it out at the link below.

Burns Statistics: A first step towards R from spreadsheets

I'm all for replicable research and a vivid R user, but I don't get it why Excel as a tool should get such a bad wrap. It's in the way the tools are used. Whenever I use spreadsheets, I comment my steps and show intermediary steps. Excel has some useful tools for debugging, such as warning you when adjacent cells contain a different formula, or if adjacent cells with numbers are not included in a formula. On the other hand, I could use the R console interactively to get statistical output and copy this into a Word document, and have nothing that's replicable.

Posted by: Claire Bird | October 29, 2013 at 16:22