Regression Analysis and Business Rules of Thumb, Essay

Regression Analysis and Business

Rules of thumb, instinct, convention, and simple financial analysis are frequently no longer adequate for addressing such common decisions found in business such as make-versus-buy, facility site selection, and process redesign. Generally, the forces of competition are commanding a need for more efficient decision making at all levels in companies. "Decision analysts provide quantitative support for the decision-makers in all areas including engineers, analysts in planning offices and public agencies, project management consultants, manufacturing process planners, financial and economic analysts and experts supporting medical and technological diagnosis"(Tools for Decision Analysis: Analysis of Risky Decisions, 2012).

Modeling for decision making comprises two distinct entities, one is the decision-maker and the other is the model-builder who is known as the analyst. The function of the analyst is to help the decision-maker in their decision-making process. Consequently, the analyst must be outfitted with more than a set of analytical methods. Specialists in model building are frequently lured to study a problem, and then go off by themselves to develop a complex mathematical model for use by the manager.Unfortunately the manager may not comprehend this model and may either use it blindly or decline it all together. The specialist may feel that the manager is too uninformed and unsophisticated to be grateful for the model, while the manager may feel that the specialist lives in a dream world of impractical assumptions and immaterial mathematical language (Tools for Decision Analysis: Analysis of Risky Decisions, 2012). The trick is to get everyone on the same page so that things can get accomplished.

Linear regression analysis is an outstanding management tool. Linear regression analysis is a method of looking at data that has two or more variables. By generating the best fit line for all the data points in a two-variable system, values of y can be forecast from known values of x. Linear regression is used in business to predict events, administer product quality and look at a diversity of data types for decision-making (Keener,….....