A p-value is a measure of the probability that an observed difference could have occurred just by random chance. The lower the p-value, the greater the statistical significance of the observed difference. P-value can be used as an alternative to or in addition to pre-selected confidence levels for hypothesis testing.

What does p-value mean in simple terms?

P-value is the probability that a random chance generated the data or something else that is equal or rarer (under the null hypothesis).

What does p-value of .9 mean?

That's pretty tiny. On the other hand, a large p-value of . 9(90%) means your results have a 90% probability of being completely random and not due to anything in your experiment. Therefore, the smaller the p-value, the more important (“significant“) your results.