Evaluate the significance of the p-value. You can think of the p-value as the probability that the null hypothesis is true. A value greater than 0.05 indicates that in more than 1 in 20 (or more than 5%) repetitions of an experiment of the same size, the observed deviation from predicted valuescould have been obtained by chance, even if the null hypothesis is actually true; the data are therefore not significant for rejecting the null hypothesis. Statisticians have arbitrarily selected the 0.05 p-value as the boundarybetween rejecting or not rejecting the null hypothesis. A p-value of less than 0.05 means that you can consider the deviation to be significant, and you can reject the null hypothesis.

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2-Proportion Test

In a 2-proportion test, two separate proportions are measured at the same time, and their similarity is evaluated. It is also known as a 2-proportion z-test, and a comparison of two different proportions is done in this method.