Statistics?

It's been so long! I've been on the go packing everything up, then driving across the country, and now that all my stuff is in one place again I can breath a little. It's nice knowing I won't be starting classes and I won't need to buy more textbooks. It's now my full time job to find a job. There are some perks to this job, I can take breaks whenever I want. Granted I have to stay focused but there's no wardrobe requirement beyond t-shirts and shorts.

So far on the job search I am trying to hone the best keywords for finding a job with my qualifications. It's helpful that John is looking for something similar because I can bounce ideas off him and him I. What I have found interesting is that I'm not sure employers know they need a statistician. I'll find postings which describe my qualifications but don't have the title of statistician, it's pretty interesting. Statistics is one of those fields that can be applied to almost anything, but the job descriptions I find are more geared towards some mislabeled "analyst" or programmer posting. As someone who does statistics, "analyst" works to describe only part of what I do. In addition to analyzing data there are so many other parts to the work: importing data, data manipulation, determining a model, then running analyses, then finding a way to present this analysis to someone who doesn't have as much of a statistical background. The way to look at it is this: A statistician may not know tons about the field their data comes from, but they can still analyze it and probably come up with a good explanation of what's going on. My hunch is that lots of employers think to themselves, "well, if they don't know anything about the field, how can they help us?". The answers lies in the fact that typically a (good) statistician takes in data and before even starting anything, forms questions about the dataset. These are questions along the lines of:

  • Where did this data come from?
  • What variables were measured?
  • How was the data collected?
  • What prediction or response was in mind when the experiment was carried out?
Once these are answered (and some others), some data manipulation can begin and with that even more questions arise that need answers before getting further in the process. What I'm tying to get across here is that statistics is not just looking at numbers, it's understanding where they came from, being able to reorganize them, and then getting into what they can tell us about a certain situation (analysis). 

I hope this sheds a little light on some who don't know much about statistics and are curious. Now it's time to continue the search for a job fit for me!

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