The introduction section of your research thesis or dissertation is the first thing that most people will read after reading the abstract. Some people use the introduction section to provide a literature review, and I won’t talk about that here. I did offer a nice recommendation on how to write a literature review in an earlier post. The introduction should provide present your research problem (research question, research hypothesis), but first you have to offer some context. Continue reading
This website will take an address, either on a form or as a batch of up to 10,000 addresses (CSV format) and provide latitude, longitude pairs as well as U.S. Census tract information. Continue reading
A rather harsh and cynical take on data science, but still worth reading. Let me share a story about this. Back in my college days (that would be the 1970s), someone found a New Yorker cartoon and shared it with me. It showed a politician, obviously a very powerful politician because his office had a view of the Washington Monument. He was speaking to his aide “That’s the gist of what I want to say. Now go and find me some statistics to base it on.” So the issues that this person brings up are no different than those from four decades ago. There’s no easy solution to the problem. You can’t say, “I’ll only work with people who have a commitment to the truth, no matter where it might lead” because even people without strong overt biases still have subtle biases that can profoundly skew the results. Requiring a priori specifications and reserving a hold out sample for a final quality check can help, but mostly it is just being careful and detail oriented and transparent in all your work. Continue reading
This is a series of guides on survey research, written for the beginning student. It is written from the perspective of Political Science, but the advice works for other areas as well. Continue reading
This is one of those articles where you have to restrain yourself. Its message, that good old statistical tools like logistic regression can perform as well as these new fangled machine learning approaches that you haven’t taken the time to learn, is quite tempting. But I’d be cautious here. Maybe logistic regression is still competitive, but maybe the systematic overview got a bunch of biased studies. It’s worthwhile to cite this whenever someone makes an overly strong claim about machine learning models, but don’t use this as an excuse to keep from learning the new stuff yourself. This article is stuck behind a paywall. Sorry! Continue reading
We live in a golden age of learning, where you find find just about anything you’d ever need to learn from on the Internet. One example of this is a series of webinars about who to get research funding through the Congressionally Directed Medical Research Programs (CDRMP). I have not listened yet to any of these webinars, but they look like they would be very helpful for anyone seeking funding through this program. Continue reading
This is actually a nice “peek under the hood” approach with lots of practical advice about getting that last tweak in to make your results go from good to great. Continue reading
You can incorporate very nice looking mathematical formulas in R Markdown fairly easily. The system relies on LaTeX for displaying formulas and is surprisingly easy to learn. But every once in a while you want to do something a bit exotic, like placing a “hat” in your equation. I’ve typically just done a quick Google search on something like “LaTeX hat symbol” and each different search yields a different website. Recently, I stumbled up a fairly comprehensive guide to displaying mathematical formulas in LaTex. It is published as an eBook.
Note: Some of the examples require additional libraries like amsmath and I haven’t figured out yet how to take advantage of these libraries in R Markdown. Continue reading
“Did you hear about the mathematician who was afraid of negative numbers? He would stop at nothing to avoid them.” (This joke is all over the Internet, and I’m not sure where the original source would be).
This is a brief plea to avoid using the word “exponential” when you really mean “a lot.” Continue reading