Writing Exercise #13

Can experiments detect differences that matter?

This question is often used to challenged the results of a study, thus making sure that what was found, is correct, and can be duplicated by other researchers.

Does the study show causation or correlation?

Often times correlation is mistaken as causation, so that is why researchers use this question to distinguish between the two. An example that I learned in my statistics class was, high ice cream sales were correlated with warmer weather; however, ice cream sales do not cause the temperature to increase outside. Understanding the difference between correlation causation is very important, especially in terms of scientific literature because it is pertinent to know what variable is causing the result.

What is the mechanism?

Asking this questions allows for the reader to have a better idea on how the study was conducted and what possible outside influence may have had a hand in the results. Often times, knowing methods of the research allow for the read to interpret whether or not the literature shows correlation versus causation.

How much do experiments reflect reality?

This questions puts the literature into real life. In other words it asks, how does this relate to readers or everyday life? For example, due to ethics, many studies can’t be done on humans, rather they are done on animals. With that being said, not all results that were produced from a study done on an animal could be applied to humans or their health.

Could anything else explain the results?

Again, this questions brings up the argument of correlation versus causation. This question explores whether or not there are any other variables that caused the result, other than the ”expected” cause.

Which is most helpful when discussing controversy

I believe the most helpful question when discussing controversy is “does the study show causation or correlation?” I think this question is the most helpful because it challenges the results and validity of a study. If the results show causation, it is a much stronger argument than if the results showed correlation.

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