how do you interpret p values and confidence intervals 
a p value is a statistical measurement used to validate a hypothesis against observed data that measures the probability of obtaining the observed results assuming that the null hypothesis is true in general a p value less than 0 05 is considered to be statistically significant in which case the null hypothesis should be rejected this can somewhat correspond to the probability that the null hypothesis value which is often zero is contained within a 95 confidence interval the bottom lineconfidence intervals allow analysts to understand the likelihood that the results from statistical analyses are real or due to chance when trying to make inferences or predictions based on a sample of data there will be some uncertainty as to whether the results of such an analysis actually correspond with the real world population being studied the confidence interval depicts the likely range within which the true value should fall 