Saturday, November 15th, 2014
Again, wikipedia sums it up
In statistical significance testing, the p-value is the probability of obtaining a test statistic result at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. A researcher will often “reject the null hypothesis” when the p-value turns out to be less than a predetermined significance level, often 0.05 or 0.01. Such a result indicates that the observed result would be highly unlikely under the null hypothesis. Many common statistical tests, such as chi-squared tests or Student’s t-test, produce test statistics which can be interpreted using p-values.
More examples of calculating the p value