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Relationships between Correlation and Causation - Article Example

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The logical fallacy implied in the paper "Relationships between Correlation and Causation" has to do with the fact that correlation between two sets of variables does not actually have an impact with regard to the primary cause that motivated these variables or occurrences in the first place…
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Relationships between Correlation and Causation
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Extract of sample "Relationships between Correlation and Causation"

Whereas it is oftentimes true that a certain level of correlation relates to a similar cause, the assumption that these two are mutually exclusive is oftentimes what leads individuals down the primrose path of expectation.

For instance, the medical researcher must be keenly aware of the fact that a correlated trend between two or more groups is not significant enough to assume that similar causation is responsible for their occurrence. Many scholars point to the fact that as drugs are tested on humans or animals, scholars oftentimes take note of unique similarities between the test groups. Oftentimes, a preliminary representation of these findings lends one to believe that joint causation must be exhibited.  However, such an assumption is more often than not incorrect and should instead cause the researcher/healthcare professional to review the data and perform further tests prior to jumping to conclusions.  Ultimately, the scientific method is predicated upon the ability of the researcher to test and prove that the findings are accurate, correct, and repeatable (Lee, 2012).

An individual that works in a chicken processing plant may notice that ambient room temperature has an impact on the overall shelf life of the chicken that is stored within the warehouse. In such a way, ambient temperature has an impact on shelf life that shelf life does not have an impact upon ambient and stops in such a way that, the relationship is causal.  By means of comparison and contrast, the relationship could be with respect to the overall exhibition of violence within a particular region as compared to the overall number of cell phone towers is not (Gelder, 2013). Whereas it may be true that a decreased number of cell phone towers are exhibited within areas that are less violent than others, the correlation does not equate to the causation of the actual reasons for this violence.

Ultimately, understanding these unique dynamics is essential for a researcher and healthcare professional to back to allow them to better understand the dynamics of by understanding these elements to a further and more complete degree, erroneous conclusions will be reduced and the implicit level of error that exists with regards to pinpointing causation for causation will further be reduced.  Without better understanding and reviewing the data, problems, and failures of understanding will continue to be evidenced; thereby necessitating individuals within research professions to be especially mindful of the fact that correlation does not necessarily equate to causation

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