Linear regression can be used for any number of business situations or business practices. It is used to see the relationship between two variables. Linear regression is a very useful tool in forecasting, and it can be applied to marketing research, accounting, supply chain management, and advertising. Simple linear regression can occur in business situations or practices where there is an independent and dependent relationship between variables. For example, a marketing manager can find the relationship between sales and the amount of money spent on advertising, where sales would be the dependent variable and advertising would be the independent variable. Simple linear regression would be used to find how much money should be spent in advertising to increase sales. In cases where the variables are independent (meaning the points on the scatter chart have no determinable pattern), simple linear regression cannot be used. For example, a human resource manager cannot predict with certainty when the people in an organization will miss a day of work due to an illness. Using the workers as one variable and the days each worker missed as another, the chart will have no real determinable pattern because each individual is different and do not get sick around the same time. Multiple regression may be better suited for such an issue.
Render, B., Stair, R. & Hanna, M., (2012). Measuring The Fit Of The Regression Model. Quantitative Analysis for Management (p. 116 – 128). Upper Saddle River, NJ: Prentice Hall – Pearson Education, Inc.
Lecture 3 (August, 2013). Grand Canyon University. Instructor: Theresa Clifton. Course: BUS-660.
Stevenson, W. & Ozgur, C. (2007) Introductions the Management Science and Forcasting. Introduction to Management Science with Spreadsheets (p. 65 – 72)