Inferential Statistics: Focus on the P Value

Abstract
As I sit at my desk, I realize it's hardly a year since my graduation in July 2016. What occupies my mind is the inconsistency with which inferences made from the utilization of P Value as an assessment of statistical significance are skewed towards biases of analysts, sometimes just a result of blatantly confusing principles of model assumption. My quick research reveals that statistics as a field experiences selective interpretation of statitics, and detrimental of them all is the probability related value, P value. This article gives an insight on the correct interpretation of P value, relative to a pre-determined level of significance for a hypothesis test. The overall theme leading to inconsistencies or inacuracies with P value is in the violation of data analysis protocols.
Find out in the full text, issues around interpretation of the P value and insights; A large P value favors Null hypotheses!
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Comments

  1. Omondi Online29 January 2023 at 20:52

    Also important here is to differentiate statistical significance from scientific significance as far as p value is concerned.

    ReplyDelete

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