Friday, July 26, 2013

Psychology 07.26.13

I'm going through Udacity's Introduction to Psychology so here are my notes. Psychology is a field of science that explores the questions of why we do what we do. Psychology covers a wide area, from developmental psychologists who study why children acquire different skills at different times to industrial psychologists who review workplace dynamics to create a more productive environment, the classic image of a Freudian character asking a patient how that made them feel is only a small part of what psychologists do.

Lesson 2 is about research methods. The first part of the lesson is about correlations. Let's say that the price of pickles went up 2 dollars and the price of milk went up 1 dollar, so looking back we can see that as the price of pickles goes up so does the price of milk. So if we were to plot the data points on the price of pickles to milk we would likely see a correlation. However, that does not mean that one caused the other, the price of milk could be going up because of the economy or higher fuel prices, pickles could be in higher demand recently or a million other things could have affected the price. Correlation does not imply causation.

To determine whether one thing causes another is often more difficult than plotting points on a graph. One way is through an experiment. A good experiment starts with a testable hypothesis. I want to know what the best time to feed my girls vegetables is, I've noticed that they tend to eat more vegetables if they have them before meals or as snacks. So my hypothesis is, My girls will eat more of their vegetables if they are fed to them before their meals. Now I set up my experiment, I will feed my children vegetables before meals one week, during meals another week and after meals another week.. The independent variable (the one I will manipulate) in this experiment is the time they are fed vegetables. I will measure how much they eat by how much is left afterwards making quantity remaining my dependent variable. To ensure that my data actually measures what I want it to measure I will control the time of day they eat, what vegetables are served, and what the environment is while they are eating (tv on or off, living room or kitchen), these are my control variables. If in fact they do eat more when they are fed veggies before meals I will have proved my hypothesis. The difference between a hypothesis and a theory is that a theory encompasses many proven hypothesis to come up with an idea that ties them all together. Saying for example that evolution is a theory is really saying that it is the best explanation we have for all the data and proven hypothesis currently available to us.  As an aside, during my hypothetical experiment I recorded measurable data (how much of the veggies were left), if I wanted to know how much my kids like veggies I would have to find a way to measure "liking a food" liking something is a construct in that we know what someone means when they say they like something but it isn't a quality that we can measure. So we use operational definitions, in this case we could say kids will eat more of the foods they like so we will measure how much they eat.

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