REGRESSION ANALYSIS

In scientific research/industrial problem solving often a situation is encountered  where in  a number of variables are involved with possible interactions or relationship among themselves.

Regression analysis is a statistical technique for investigating and modeling relationship among these variables in such situations. As an example, consider the Current and Plating Thickness in electroplating. One may be interested to find out whether they are related and if so, what is the form of relationship. The relationship may be expressed in the form of an equation or model connecting one of the variables, known as the response or the dependant variable (denoted as Y) with one or more other variables known as explanatory or predictor or independent variables (denoted as X or X1, X2,X3 etc.).

The variables can be either quantitative or qualitative.  Examples of quantitative variables are measurable variables like hardness, tensile strength, diameter, width,  etc. Examples of qualitative variables are good/bad, defective/non-defective, religion, sex, region etc  

Applications of regression analysis are numerous and occurs almost every field, including engineering, quality control, physical and life sciences, economics, management, social sciences etc.