# As access to computers becomes more and more prevalent, we see the P-value reported in hypothesis testing more frequently. Review the use of the P-val

As access to computers becomes more and more prevalent, we see the P-value reported in hypothesis testing more frequently. Review the use of the P-value in hypothesis testing. What is the difference between the level of significance of a test and the P-value? Considering both the P-value and level of significance. under what conditions do we reject or fail to reject the null hypothesis?
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In statistical hypothesis testing, the P-value or probability value or significance value provides the basis for deciding whether or not to reject ${H}_{0}$. The P-values is the probability that a test statistic will take on values as extreme or more extreme than the test statistic computed from the random sample assuming that ${H}_{0}$ is true. The value of level of significance a is associated with confidence level of our test.
There are two conditions for P-values that we reject or fail to reject the null hypothesis.
If $P-value\le \alpha$, we reject ${H}_{0}$ and say that the data are statistically significant at the level $\alpha$.
If $P-value>a$, we do not reject ${H}_{0}$.