Assuming that the null hypothesis is true, the is the probability of observing a value of the test statistic that is at least as extreme as the value actually computed from the sample data.

p-value                                                                                                  

Explanation:

p-value: In statistics, the term p-value is defined as the probability of getting the observed results of a particular test, which leads to the assumption that the null hypothesis of the research or test is correct. p-value describes the level of marginal significance that underlies in a statistical hypothesis test that represents an event's occurrence probability.

In any of the statistical analyses, if the p-value is considered as less than 0.05 then the null hypothesis is being rejected and it is explained that there's no seen difference between two different means and hence a conclusion is made describing that a significant difference exists.

In the question above, the statement signifies the significance of the p-value.

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