Data Preparation
Before forecasting is performed, the data being used must be “prepared”. If the data contains errors, then the forecast result will be equally flawed. It is therefore vital that all anomalous data be removed. Such a procedure is known as data “scrubbing”. Scrubbing data involved removing data points known as “outliers”. Outliers are data that lie outside the normal pattern. They are usually caused by anomalous and often unique events and so are unlikely to recur. Removing outliers improves data integrity and increases the accuracy of the forecast.
Read more about this topic: Telecommunications Forecasting
Famous quotes containing the words data and/or preparation:
“Mental health data from the 1950’s on middle-aged women showed them to be a particularly distressed group, vulnerable to depression and feelings of uselessness. This isn’t surprising. If society tells you that your main role is to be attractive to men and you are getting crow’s feet, and to be a mother to children and yours are leaving home, no wonder you are distressed.”
—Grace Baruch (20th century)
“With memory set smarting like a reopened wound, a man’s past is not simply a dead history, an outworn preparation of the present: it is not a repented error shaken loose from the life: it is a still quivering part of himself, bringing shudders and bitter flavours and the tinglings of a merited shame.”
—George Eliot [Mary Ann (or Marian)