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Writing Exercise #13

Can experiments detect differences that matter?

This question asked by readers of scientific literature is important because it seeks to ensure the results used to make a conclusion are valid. In the field of microbiology, for example, this can be seen when trying to understand functional differences between closely related genes versus sequences.

Does the study show causation or correlation?

This question is important to ask because while there may be correlation, it can be difficult to prove causation. One example which I have been always told, is that ice cream consumption is correlated with pool drownings. While these are correlated, it is clear that eating ice cream does not cause you to drown. Instead, there is a confounding variable of warmer weather; when it is sunny outside, there is both increased ice cream consumption and frequency of pool usage, and thus increased incidence of drowning. This can be applied to scientific literature because correlation almost always insists some type of causation, but the direct cause can be hidden or covered in the variables studied.

What is the mechanism?

This question asks readers to understand the conclusions on a deeper level before interpreting and analyzing the claims made by the scientific literature. Thus, understanding the mechanisms can help to determine if the study shows causation or correlation.

How much do experiments reflect reality?

This question serves to address the differences between the research in scientific literature and real life. For example, many studies cannot exactly replicate human microbiome, and use animal models or human cells. Thus, the results may not exactly translate to human health mechanisms. A general example which is common, is comparing the virulence factors of some bacteria is varying effectiveness in in-vivo and in-vitro studies.

Could anything else explain the results?

This question further explores the idea of correlation versus causation. Thus, it seeks to find other plausible confounding variables which influence the results found.

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