 When you're doing your data sourcing and you're making data sometimes you can't get what you want through the easy ways And you got to take the hard way and you can do what I'm calling laboratory Experiments now of course when I mentioned laboratory experiments people start to think of stuff like you know, Dr. Frankenstein in his lab But lab experiments are less like this and in fact, they're a little more like this Nearly every experiment I have done in my career has been a paper and pencil one with people in a well-lighted room And it's not been the threatening kind now the reason you do a lab experiment is because you want to determine cause and effect and This is the single most theoretically viable way of getting that information Now what makes an experiment an experiment is the fact that researchers play active roles in Experiments with manipulations now people get a little freaked out when they hear manipulations things that you're coercing people and messing with their mind All that means is you are manipulating the situation. You're causing something to be different for one group of people or one situation than another It's a benign thing, but it allows you to see how people react to those different variations Now you're gonna want to do an experiment you're gonna want to have focused research It's usually done to test one thing or one variation at a time and it's usually hypothesis driven Usually you don't do an experiment until you've done enough background research to say I expect people to react This way to the situation in this way to the other a key component of all of this is that experiments almost always have random Assignments so regardless of how you got your sample when they're in your study You randomly assign them to one condition or another and what that does is it balances out the preexisting differences between groups? And that's a great way of taking care of confounds and artifacts the things that are unintentionally associated with differences between groups that provide alternate Explanations for your data if you've done good random assignment and you have a large enough people then those confounds and artifacts are basically minimized Now some places where you're likely to see a laboratory experiments in this version are for instance Eye tracking and web design. That's where you have to bring people in front of a computer and you stick a thing there That sees where they're looking That's how we know for instance that people don't really look at ads on the side of web pages another very common place is research and medicine and Education and in my field psychology and in all of these what you find is that experimental research is considered the gold Standard for reliable valid information about cause and effect on the other hand Well, it's a wonderful thing to have it does come at a cost. Here's how that works number one Experimentation requires extensive specialized training. It's not a simple thing to pick up To experiments are often very time-consuming and labor-intensive I've known some that take hours per person and number three experiments can be very expensive So what that all means is you want to make sure that you've done enough background research and you need to have a situation where it's sufficiently important to get really reliable cause and effect information to justify these costs for experimentation in some Laboratory experimentation is generally considered the best method for causality or assessing causality That's because it allows you to control for confounds through randomization On the other hand, it can be difficult to do So be careful and thoughtful when considering whether you need to do an experiment and how to actually go about doing it