Data Monster

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The Data Monster awoke hungry and angry. She rose out of the dark, damp Cave of Quantitative Remorse and blinked her bleary eyes. She was searching for something, if only her sleep-slowed brain could remember what it was...oh yes, breakfast! With her new goal firmly affixed in her mind, her eyes scoured the plush lands of Qualitative Research World. Where would she find something to eat at this hour? Ah, yes...in Year5--a tiny neighborhood in the TenureTrack division of Qualitative Research World. Why should she go to Year5? Because it had the easiest people to eat! They were slow, groggy, focused with a delightfully distracted air, and they sometimes wandered too close to the Cave of Quantitative Remorse. 


The Data Monster turned her massive head slowly, her eyes becoming rapidly clear as she spied one lone researcher wandering too near the Quantitative realm. Why on earth would this pathetic figure attempt to navigate Quantitative landscape? She obviously belonged in Qualitative Research World...her excursion into the Data Monster's turf was not her first, but her survival skills were lacking, her knowledge incomplete. Without a doubt, breakfast was served. Data Monster swooped in and, in one swift movement, clasped a talon-filled claw around the poor Year5, who would soon be out of her misery.

Yes, despite my training in qualitative analysis, I have several projects that have emerged with quantitative data. While I have no objection to quantitative analysis, I most frequently employ qualitative analysis and have found myself rather rusty and (gasp) unclear on the quantitative maneuvers now required of me. I feel that there is a giant road block in the way -- blocking the END of several projects. I can see the end, I even know (roughly) how to get there, I just forget how to move over the terrain. Isn't that sad? Projects stalled by my own lack of ability...and in year 5 of the tenure-track I have absolutely no time for projects to be stalled or delayed.

Situations like this (I expect and in a sick way rather hope) have happened to others. I don't want to be alone in this silly move to switch from one area of comfort and knowledge to a less known, less comfortable area. Resolving such situations can be tricky. Do I seek assistance, tutoring, lessons and read every book from my long-past classes in statistics class? (CHECK!) Do I ask someone on campus in a more quantitatively inclined field? (CHECK!) Do I sit and bemoan my situation as I feel my research progress grind to a halt? (CHECK!) These efforts to overcome my inept ability have put me on the time lines of others, left me waiting with hope and commitments only to later be turned down, disappointed, and another week or two delayed as first one person, then another, tells me they can and will help only to later change their minds. Their choices are understandable. We are all busy. It doesn't make it any easier. Navigating the quantitative (or qualitative) realm after working so long in the qualitative (or quantitative) one can challenge any researcher. It is exciting to learn new skills and explore data in a new way, but it is also difficult during the middle of a busy semester.

I have employed the options above and now feel stuck, again, waiting and hoping for some grain of knowledge to magically appear as I re-read my stats text from ten years ago -- perhaps that knowledge will come, dressed as a shiny, silver Knight brandishing a sword (suspiciously shaped like an obscure statistics symbol) ferociously bellowing his presence to save me from the clutches of the Data Monster--who is at this time holding me hostage in the Cave of Quantitative Remorse.

Of course, I know I can and will, save myself. The question is, can I do it in time?

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