A statistical analysis performed to determine the origin of random data figures collected. Random factor analysis is used to decipher whether the outlying data is caused by an underlying trend or just simply random occurring events and attempts to explain the apparently random data. It uses multiple variables to more accurately interpret the data.
This data is used to help companies better focus their plans on the actual problem. If the random data is caused by an underlying trend or random norecurring event, that trend will need to be addressed and remedied accordingly. For example, consider a random event such as a volcano eruption. Sales of breathing masks may skyrocket, and if someone was just looking at the sales data over a multi-year period this would look like an outlier, but analysis would attribute this data to this random event.