- Published on December 19, 2018
- In AI Features
Beware Of Statistical Significance: What The P value Really Tells Us
- By Mayank Gupta
The American Statistical Association (ASA) gathered more than two dozen experts to develop a consensus on statistical significance and p-values and issued a statement on it in 2016. But what prompted the ASA for the very first time to issue such a statement which deals with the specific matters of statistical practice. The p-value is defined as the probability, under the assumption of no effect or no difference (which is also known as the null hypothesis), of obtaining a result equal to or more extreme than what you actually observe. The father of modern statistics RA Fisher who introduced p-values as formal research tool proposed to attach the term significance to low p-values which as the term itself suggest worthy of attention in the form of warranting more experiment but not a proof it
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Mayank Gupta
Mayank Gupta is a Research Scholar working in the field of Statistics & Econometrics at Mumbai School of Economics And Public Policy (Autonomous), University of Mumbai.
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