Regression and Correlation Analysis

Observing and establishing the relationships between variables is one of the most important tools for scientific research. Regression and correlation are concerned with the relationship between two or more variables. A correlation measures the degree of dependency of two variables. While correlation establishes a degree of relationship, it does not specify the kind of relationship; this is the aim of regression. A regression is the quantitative description of the relationship using a mathematical function. A regression analysis has at least two steps: the determination of a regression model and the estimation of the regression coefficients. The regression model is the type of function of the independent variable defining the general shape of the regression curve, while the regression coefficients define the actual shape of the regression curve. Interpolation estimates the value of a dependent variable based on an independent variable and uses regression techniques.