Data Mining Applications Discussion Board

Posted: August 27th, 2021

Data Mining Applications Discussion Board

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Data Mining Applications Discussion Board  

The article by Ioannidis and other researchers summarizes why most published research works tend to be untrue in their findings and conclusions. With such concern in mind, Loannidis et al. (2001) illustrate how the possibility of finding a false research claim is entirely dependent on the probability of it being true. Precisely, the article states that the study bias and power, the number of research papers on similar topics, and the true-to-no relationship ratios are potential factors that would affect the level of trueness in scientific fields.Notably, several approaches can improve the probability of truth in post-studies, such as using good powered evidence like low-bias meta-analyses. Hence, this evidence has to be targeted for study questions with considerable probability for a pre-study. As such, the findings of the study would contribute to a post-test probability that is considered quite definitive.  Undeniably, it is impossible to tell with one hundred percent certainty, the truth in any research question. Also, it has become difficult to attain the desired research standards. Thus, using enhanced standards of research can help reduce biases in a study.

Furthermore, from the hypothesis development, one can adduce that research findings and conclusions are less likely to be true if the number of other studies conducted on the same topic is low. Thus, upfront registration of various studies is vital since it would pose a challenge for research that generates hypotheses.

More so, an article on Harvard Business Review by Winsborough and Chamorro-Premuzic (2017)shows that an increased number of participants would negatively affect the findings. This is because emotional intelligence levels and degree of communication are subject to constant conflicts. Therefore,to attain true findings and avoid conflicts of interest, the number of participants should be minimized.

References

Ioannidis, J. P., et al. (2001). Any casualties in the clash concerning randomized and observational evidence? BMJ, 322, 879-880.

Winsborough, D., & Chamorro-Premuzic, T. (2017, January 25). Great teams are about personalities, not just skills. Harvard Business Review. https://hbr.org/2017/01/great-teams-are-about-personalities-not-just-skills