Essay Quasi-Experimental Design

Essay Quasi-Experimental Design-52
You know that you seek a room marked with the numbers 1-0-1-2, so you press the button marked "10." The halves slide shut and enclose you within the cubicle, which jolts upward. A ride in an elevator may not seem like an experiment, but it, and each step taken towards its ultimate outcome, are common examples of a search for a causal relationship-which is what experimentation is all about.You started with the hypothesis that this is in fact an elevator. You then hypothesized that the button to summon the elevator was on the left, which was incorrect, so then you hypothesized it was on the right, and you were correct.

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You approach a stainless-steel wall, separated vertically along its middle where two halves meet.

After looking to the left, you see two buttons on the wall to the right. A soft tone sounds and the two halves of the wall slide apart to reveal a small room. Looking to the left, then to the right, you see a panel of more buttons. On the far wall, a sign silently proclaims, "10th floor." You have engaged in a series of experiments.

Matching may be problematic, though, because it "can promote a false sense of security by leading [the experimenter] to believe that [the] experimental and control groups were really equated at the outset, when in fact they were not equated on a host of variables" (Jones, 291). This method is based on the statistical principle of normal distribution.

In other words, you may have flowers for your Mega Gro experiment that you matched and distributed among groups, but other variables are unaccounted for. Theoretically, any arbitrarily selected group of adequate size will reflect normal distribution.

The term treatment refers to either removing or adding a stimulus in order to measure an effect (such as turning the knob a little or a lot, or reducing the noise level a little or a lot).

Experimental researchers want to know how varying levels of treatment will affect what they are studying.

As such, researchers often have an idea, or hypothesis, about what effect will occur when they cause something.

Few experiments are performed where there is no idea of what will happen.

In this example, even though the designers of the experiment have tried to remove all extraneous variables, results may appear merely coincidental.

Since the goal of the experiment is to prove a causal relationship in which a single variable is responsible for the effect produced, the experiment would produce stronger proof if the results were replicated in larger treatment and control groups.


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