Identifying credit cards usage pattern using multiple regression analysis

Regression analysis is by far the most widely used and versatile dependence technique, applicable in every facet of business decision making. Multiple regression analysis is a statistical technique that can be used to analyze the relationship between a single dependent (criterion) variable and several independent (predictor) variables. A small study of 35 families from Ahmadabad regarding their credit cards usage are taken to determine which factors affected and correlated with each other. The objective of the study was to determine which factors affected the number of credit cards hold by people in ahmedabad city. Three potential factors were identified family size, family income and number of vehicles owned. The objective of multiple regression analysis is to use the independent variable whose values are known to predict the singe dependent value selected by the researcher.

The above estimated regression equation indicates that the family size is negatively related with credit cards. Similarly the income and number of vehicles are positively related to the credit cards. The results indicated that the family size significantly influences credit cards usage where as the impact of income and number of vehicles upon credit card usage insignificant.