A simple regression analysis can show that the relation between an independent variable and a dependent variable is linear, using the simple linear regression equation.

This statistical tool is used to develop the equation that represents the relationship between the variables. Regression analysis is a powerful statistical technique that identifies the association between two or more quantitative variables: a dependent variable, whose value is to be predicted, and an independent or explanatory variable (or variables), about which significant amount of knowledge is available. At the same time, the researchers also assess the “statistical significance” of the estimated relationships, that is, the degree of confidence that the true relationship is close to the estimated relationship.

effect of income on expenditure or effect of changes in money supply on the rate of inflation. In some situation, researchers are interested to determine the underlying effect of one variable on another variable viz. Regression analysis is a statistical technique to investigate the relationships between quantitative variables. The paper also briefs about various statistics associated with multiple regression analysis. This term paper talks about the concept of multiple regression analysis, its assumptions, application, and its limitations to the social science research. Although we have freedom to select research tools for multivariate analysis as wide range of research tools are available, multiple regression analysis allows us to determine the effect of more than one independent variable on dependent variable. Researchers often come across the situations where they want to study the impact of one variable on the other variable viz. This is well known fact that the success of social science research heavily depends upon the selection of research tools and its effective utilization. MULTIPLE REGRESSION ANALYSIS: KEY TO SOCIAL SCIENCE RESEARCH Abstract

Scientific regress