Linear regression analysis is a method of analyzing data that has two or more variables. By creating the "best fit" line for all the data points in a two-variable system, values of y can be predicted from known values of x. Linear regression is used in business to predict events, manage product quality and analyze a variety of data types for decision-making.
Trend Line Analysis
Linear regression is used in the creation of trend lines, which uses past data to predict future performance or "trends." Usually, trend lines are used in business to show the movement of financial or product attributes over time. Stock prices, oil prices, or product specifications can all be analyzed using trend lines.
Risk Analysis for Investments
The capital asset pricing model was developed using linear regression analysis, and a common measure of the volatility of a stock or investment is its beta--which is determined using linear regression. Linear regression and its use is key in assessing the risk associated with most investment vehicles.
Sales or Market Forecasts
Multivariate (having more than two variables) linear regression is a sophisticated method for forecasting sales volumes, or market movement to create comprehensive plans for growth. This method is more accurate than trend analysis, as trend analysis only looks at how one variable changes with respect to another, where this method looks at how one variable will change when several other variables are modified.
Total Quality Control
Quality control methods make frequent use of linear regression to analyze key product specifications and other measurable parameters of product or organizational quality (such as number of customer complaints over time, etc).
Linear Regression in Human Resources
Linear regression methods are also used to predict the demographics and types of future work forces for large companies. This helps the companies to prepare for the needs of the work force through development of good hiring plans and training plans for the existing employees.
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