Regression analysis can be defined as the process of developing a mathematical model that can be used to predict one variable by using another variable or variables. This section first covers the key concepts of two common approaches to data analysis: graphical data analysis and correlation analysis and then introduces the two main types of regression: linear regression and non-linear regression. The section also introduces a number of data transformations and explains how these can be used in regression analysis.
Advertising cost and Amortization example
It is well known that some form of advertising and amortization for a particular product or company will be associated with and have an effect on its Revenue.Numerical data has been collected from ten companies on their monthly volume of revenues of a particular product as well as their cost of advertising and amortization of company. This data is shown in table .We want to develop an appropriate regression model that will be based on this data and could be used to predict the volume of sales for a particular company, given that company’s advertising cost and amortization cost.