Perfecting Linear Regression Predictions - Assignment Example

 Using regression analysis for predicting quarterly purchases of building materials may not yield accurate results because of many factors such as the rise of unpredictable situations, the duration in which data points are taken, and the number of variables used for regression analysis.

First, regression analysis uses data from past events and therefore may not be accurate if an unaccounted event occurs. For instance, a natural catastrophe such as an earthquake may stall all building constructions in a given area forcing customers to stop buying. If linear regression uses previous data where catastrophe was absent, then its outcome will be inaccurate. Such errors can be avoided by adding as many variables as feasibly possible to the regression model used (Montgomery, 2011).