Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 5 4 2020 07 22 259 267 Abhaya Indrayan Department of Clinical Research, Max Healthcare Institute, New Delhi, India. 2019 10 23 2020 06 20 Background: Small P-values have been conventionally considered as evidence to reject a null hypothesis in empirical studies. However, there is widespread criticism of P-values now and the threshold we use for statistical significance is questioned. Methods: This communication is on contrarian view and explains why P-value and its threshold are still useful for ruling out sampling fluctuation as a source of the findings. Results: The problem is not with P-values themselves but it is with their misuse, abuse, and over-use, including the dominant role they have assumed in empirical results. False results may be mostly because of errors in design, invalid data, inadequate analysis, inappropriate interpretation, accumulation of Type-I error, and selective reporting, and not because of P-values per se. Conclusion: A threshold of P-values such as 0.05 for statistical significance is helpful in making a binary inference for practical application of the result. However, a lower threshold can be suggested to reduce the chance of false results. Also, the emphasis should be on detecting a medically significant effect and not zero effect.   https://jbe.tums.ac.ir/index.php/jbe/article/view/310 https://jbe.tums.ac.ir/index.php/jbe/article/download/310/240