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Linear regression analysis is a method of analyzing data that has two or more variables. By creating a “best fit” line for all data points in a two-variable system, the 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 creating trend lines, which uses data from the past to predict performance or “trends” in the future. Typically, 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 be analyzed using trend lines.

## Risk analysis for investors

The capital asset pricing model was developed using linear regression analysis, and the common measure of volatility for a stock or investment is its beta (which is determined using linear regression). Linear regression and its use is critical to assessing the risk associated with most investment vehicles.

## Sales or market forecasts

Multivariate linear regression (with more than two variables) is a sophisticated method of preventing sales volumes or market movement in order to create comprehensive plans for growth. This method is more accurate than trend analysis since the latter only observes how one variable changes with respect to another, where this method analyzes how one variable will change when other variables are modified.

## Total quality control

Quality control methods often use linear regression to analyze key product specifications and other measurable parameters of product or organization quality (such as the number of customer complaints over time, etc.).

## Linear regression in human resources

Linear regression methods are also used to predict future demographics and types of workforce for large companies. This helps companies prepare for the needs of the workforce through the development of good hiring plans and training plans for existing employees.