p refers to the proportion of sample elements that have a particular attribute. q refers to the proportion of sample elements that do not have a particular attribute, so q = 1 – p.Click to see full answer. Also to know is, what are P and Q values?A p-value is an area in the tail of a distribution that tells you the odds of a result happening by chance. A Q-value is a p-value that has been adjusted for the False Discovery Rate(FDR). The False Discovery Rate is the proportion of false positives you can expect to get from a test.Additionally, what is Q hypothesis testing? q-value and p-value. The q-value of an individual hypothesis test is the minimum FDR at which the test may be called significant. One approach is to directly estimate q-values rather than fixing a level at which to control the FDR.” Also to know, how do you find the Q value? Thus the Q-value equation is literally the expected false positives based on the P-value, divided by the total number of positives actually accepted at that same P-value. You can use the Q-value much like a P-value. For example, you might choose to accept all results with a Q-value of 0.25 or less.What does P mean in statistics?In statistics, the p-value is the probability of obtaining the observed results of a test, assuming that the null hypothesis is correct. It is the level of marginal significance within a statistical hypothesis test representing the probability of the occurrence of a given event.