How do you interpret p value of a test and what does it tell

How do you interpret p value of a test and what does it tell you?

Solution

Sol)

P values evaluate how well the sample data support the devil’s advocate argument that the null hypothesis is true. It measures how compatible your data are with the null hypothesis. How likely is the effect observed in your sample data if the null hypothesis is true?

A low P value suggests that your sample provides enough evidence that you can reject the null hypothesis for the entire population.

In technical terms, a P value is the probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of the null hypothesis.

For example, suppose that a vaccine study produced a P value of 0.04. This P value indicates that if the vaccine had no effect, you’d obtain the observed difference or more in 4% of studies due to random sampling error.

P values address only one question: how likely are your data, assuming a true null hypothesis? It does not measure support for the alternative hypothesis. This limitation leads us into the next section to cover a very common misinterpretation of P values.

Interpretation:

If P> alpha we accept the null hypothesis. otherwise we reject the null hypothesis