Question

Explain the differences between the regression model, the regression equation, and the estimated-regression equation. Discuss the application of regression analysis in business decision making. Give examples on how the regression analysis can be used in business.

Answer 1

A regression model is used to investigate the relationship between two or more variables and estimate one variable based on the others.

A regression equation is used in stats to find out what relationship, if any, exists between sets of data.The equation represents the regression line,which is the “best fit” line for the data.We basically draw a line that best represents the data points. It’s like an average of where all the points line up. In linear regression, the regression line is a perfectly straight line.

Using the Least squares method estimates, an estimated regression equation is constructed using the given data:

y= b₀ + b₁x

Application of regression analysis in business decision making

- The most common use of regression in business is to predict events that have yet to occur. Demand analysis, for example, predicts how many units consumers will purchase.

- Predicting the number of shoppers who will pass in front of a particular billboard or the number of viewers who will watch the Super Bowl may help management assess what to pay for an advertisement.

- Insurance companies heavily rely on regression analysis to estimate how many policy holders will be involved in accidents or be victims of burglaries