P-Values and Z-Scores

A P-Value represents the probability that the data you have collected is due to chance.  This helps you determine whether or not there is a real difference between your observations and the norm.

The P-Value is calculated by converting your statistic (such as mean / average) into a Z-Score.

Z = (X – AVG(X) ) / Std(X)

Using that z-score, look up that value in a standard normal table.  If that value is above your desired confidence level, you can reject your null hypothesis and accept your alternative hypothesis.

The p-value is one of the most frequently reported statistic since it denotes whether a researcher’s hypothesis is statistically significant or not.

If you want to be 95% confident that your hypothesis is valid (i.e. you only have a 1 in 20 chance of being wrong), the results from your z score conversion must be greater than 95%.