Just Enough Knowledge to be Dangerous

{A dilettante-level guide to data analysis or educators}

Note: Pretty much everything that follows is a gross approximation, and is almost certainly less-than-correct to anyone who would consider themselves to be a data-analysis or statistical expert. If that’s you, then I ask your forgiveness. But you aren’t my target audience, and besides I’ve just warned you.

It’s the time of year when the data from various, standardized, terminal course exams comes rolling in. In my life, that mostly takes the form of student scores on science Regents exams. And if you’re like me, the task of analyzing that data might seem a bit overwhelming. Strings of numbers can have that effect. Compounding the issue is the seeming unavailability of any resource on how to analyze exam data that makes any real sense.

With that in mind, I’ve started working on a bit of a user guide to data analysis for .... It’s very much still a work in progress, and I could see it expanding into a variety of other realms than the aggregate exam score analysis that’s up there right now, but since I’ve been working on it a bit over the past few days, I figured now would be a good time to share it with the larger readership. Just don’t get too upset should the current organization mutate over time as I add more to it, and the feedback starts trickling in.

And if you do have any feedback, on this or anything else, don’t hesitate to send it along.