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Lurking variable example: A study found that there is a large positive correlation between the number of pharmacists and the number of deaths across American cities. Which of the following is the best conclusion?

A. Pharmacists cause deaths
B. Common cause hypothesis
C. Random chance
D. No correlation

User Neimsz
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Final answer:

Correlation does not imply causation, so it would be incorrect to conclude that pharmacists cause deaths based on a positive correlation between the number of pharmacists and the number of deaths across American cities. A lurking variable, such as population size, could explain the correlation. Further research is needed to determine the true cause.

Step-by-step explanation:

Correlation does not imply causation, so it would be incorrect to conclude that pharmacists cause deaths based on a positive correlation between the number of pharmacists and the number of deaths across American cities. This situation can be explained by a lurking variable, also known as a confounding variable, which is a third variable that affects both variables of interest and explains the correlation.

For example, it is possible that cities with higher populations have more pharmacists and also more deaths simply due to the larger number of people living there. In this case, the lurking variable would be population size. It is essential to consider other factors and conduct further research to determine the true cause of the observed correlation.

User Ahmed Salem
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