Communicating Statistical Evidence
"The biggest rule to follow for these scientific communications is to be very clear about the implications of the study being discussed."
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Through out my life, I have always been a logical and scientific thinker. As my academic career advanced, I found a passion as a Quantitative Sciences major, concentrating in neuroscience and behavioral biology. Between these two fields, I have done and read a considerable amount of scientific papers, focusing on how the evidence is presented and analyzed. Evidence is typically presented in the form of data tables or graphs after using the scientific method and clear hypotheses to arrive at the data. The use of the evidence is the most exciting part of communication and dissemination of discoveries in science. There are many ways in which the evidence could look convincing, but it is important to consider every possible way that the evidence may be misleading or contain a confound.
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Communication of scientific data is most often found via scientific reports, but is also commonly seen in news articles. The biggest rule to follow for these scientific communications is to be very clear about the implications of the study being discussed. Researchers and especially news writers are very quick to draw conclusions or make incorrect inferences and correlations about the data at hand. Proper scientific articles on observational studies, and even some experimental ones will always conclude by letting the audience know that their data may provide convincing evidence, but is not grounds to make causal inferences. This is a common theme among all observational studies, which are usually communicated to a larger audience via news articles. These news articles are commonly distributed on the Internet, and shared to many social media platforms.
It is important to tailor the level of detail to the type of audience reading the communication, but it is also important for the reader and audience to be able to detect false correlations in the article. |