On p -Values and Statistical Significance.

In particular, the data allow us to calculate the I p i -value, which is defined as " I the probability under a specified statistical model that a statistical summary of the data would be equal to or more extreme than its observed value i " [[1]], and practically reflects the degree of data compatibility with the null hypothesis. (2) " I p-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone. i " They can only tell us how consistent the data are with the null hypothesis. Conventionally, if the I p i -value is lower than the 0.05 significance level, we reject the null hypothesis and accept the alternative hypothesis. At the beginning of our research training, we learned about hypothesis testing, I p i -values, and statistical inference. [Extracted from the article]