In this tutorial, you're going to learn about data collection. Now data collection deals with not only obtaining data, but also looking at it in published articles, as well.
So, when you look at published data, it is important to look at it critically. You have to think about the who, what, where, when and why of the situation. Were there problems in defining or measuring the variables of interest? Did they have problems with trying to figure out what was going to be measured or how to measure it? For whom was the data gathered? Was this done for an independent agency or was this done for a company? Is the company that funded it trying to push a product?
So, there's all sorts of things that you can think about when you think about who actually was sponsoring this study. When was it gathered? Is it out of date? If it's out of date, then maybe you don't want to use it, because maybe there's something a little bit more recent, and a little bit more reliable out there.
Why did they do it? What are they trying to prove? They might be having an agenda here. And were any biases present in the study? And these might be biases that the researchers overlooked. But what do you do, once it's already published, once all the data has already been collected? Well, in the academic world, many people will examine and judge the study prior to it being published. If no major flaws are found, then that's evidence of a well-done study.
Basically, the more eyes you can get on the study, the better. And this is a form of quality control, and it's called peer review. What it means is you take other individuals from within your discipline, and have them critique your study. And if they can't find any big problems with it, then that's a good thing. And the majority of scholarly articles are, in fact, peer-reviewed prior to being published. And then once they're published, more people can weigh in on what they see. And it seems really harsh to critique someone's work like this, without having done the experiment yourself. But ultimately it's a good thing because maybe there'll be a follow-up experiment, and the feedback provided will make the subsequent research more well done.
And so to recap, when multiple people examine studies, and they do it critically, the study undergoes intense consideration by experts in the field. This is called peer review, and when multiple experts look at the study, they can find something that's out of whack. If they don't see something that's out of whack, that's evidence of a well-done study. And so the terms we used were data collection, quality control, and the idea of peer review. Good luck and we'll see you next time.