Causational Research

Causation research is more often called the experimental method. What makes this so important in science is that it is the ONLY way to show cause and effect. Trying to show that one thing causes another thing to change is really hard to do.

Let us take an example. I have noticed that when my kids eat hard boiled eggs, they get gas. So over time, I have come to the conclusion that eggs cause farting.

If I wanted to prove that eggs CAUSE gas then I have to set up a true experiment. The hard part is proving that the eggs actually CAUSE the gas and nothing else could have produced the farts but the eggs.

Experiments can be divided into laboratory experiments and field experiments. Laboratory experiments are conducted in a lab, a highly controlled environment, while field experiments are conducted out in the world. The extent to which laboratory experiments can be controlled is their main advantage. The advantage of field experiments is that they are more realistic.

Ok- we are going to try to prove that eggs cause gas in an experiment through a series of steps outlined below. Please note that no experiment is ever perfect and this is FAR from it.

Step One: Come up with an hypothesis. In this case we will say “Eggs cause farts”…..pretty simple.

Step Two: Identify the population you are going to study. In this case we will study Harrison High School students. But giving everyone eggs at Harrison and smelling their farts would be impossible. So we are going to have to randomly select a small group from Harrison High School students (let us select 40 kids out of a hat). Then we will randomly assign the 40 kids into two groups of twenty. We will call one group the experimental group and one group the control group.

Step Three: Identify your variables. In any experiment there are at least three types of variables. This is where it gets complicated so pay attention.

First, there is what we call an Independent Variable (IV). The IV is the thing you are going to manipulate in the experiment. It is whatever some people get and some people do not. The IV is supposed to cause change in the experiment. Another way of putting it is that the IV is what the experimental group will get and the control group will not. In this case, one group of students will get eggs (experimental group) and one group will not (control group). So the Independent Variable is the EGGS!!!!
Second there is the Dependent Variable (DV). The DV is what you are measuring in the experiment. What are you looking for? The dependent variable is called as such because it is dependent on the independent variable. In other words, the IV will cause change in the DV. So what are we measuring in this experiment? Farts!!!! The DV is farting because it depends on eggs (the IV).
A third type of variable is called extraneous or confounding variables (these are basically the same thing). These variables are BAD and we do NOT want them in our experiment. Extraneous or confounding variables are anything that causes changes in the dependent variable that is not the independent variable. In other words, anything that causes more farts that is not eggs is an extraneous variable. If our sample of students used Beano (anti gas medication) that would effect how much gas they have.

If one of our students had diarrhea, it would effect their farting behaviors and it would have nothing to do with the eggs. Remember, the object is to prove that eggs cause the gas, and if anything else could have caused the gas, it messes up our study. There is no way to eliminate all confounding variables, thus no experiment is perfect.

Step Four: Operationalize the variables. This is a complicated way of stating exactly what you mean by your hypothesis. In other words, turning your idea into real life steps. What do you mean by eggs? Scrambled, hard boiled, poached? Two eggs, four eggs etc…? What do you mean by farts? Smelly farts? Long farts? Wet Farts? When you operationalize your variables you have to be VERY specific. The reason is that if some scientist from Finland or Texas wanted to replicate your experiment, he or she would have to know exactly what you did. In the case of our experiment let us operationalize eggs by saying two hard boiled eggs on an empty stomach. Let us operationalize fart by saying three or more farts within the hour of eating the eggs that cause a noticeable foul odor.

Ok….now that you have everything in place. You need to actually do the experiment. So you have two groups, the experimental group and the control group. Now there are bunch of things you can do…here is one possibility.

You tell both groups not to eat anything for four hours before they come in (trying to eliminate some of those extraneous variables). You give the subjects in the experimental group each two hard boiled eggs (IV). You give the subjects in the control group fake hard boiled eggs (a placebo) or nothing. Obviously neither group knows why they are eating the eggs or fake eggs because that might bias the experiment (blind study). Then you wait a few hours and start to measure their farts. You can do this by either asking them if they farted, using a fart bag (it actually exists) or just smelling their behinds. Hopefully the group that had the eggs (the IV) farted more than the group that had the placebo.

This is a machine developed by students at Cornell University that measures the intensity of farts. It does this by measuring the smell (hydrogen sulphide), the sound (amplitude) and the temperature (kinetic energy). Let it not be said that great things happen at college and your parents’ money is well spent!!!!

Sometimes scientists have biases in their studies that they might not be aware of. Think about it, you really want your study to be successful, so maybe you smell a little bit more intensly to those you know had the eggs. This would not be fair. To eliminate these types of biases, many scientists use what they call a double-blind study. Here, the scientist is not aware who had the eggs and who had the placebo, so the measuring of the DV occurs without bias.

Once you tabulate your results (measure you dependent variable), you must show the world your results through the wonderful language of statistics.