BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -The simplest form of the regression equation with one dependent and one independent variable is defined by the formula y = c + b*x, where y = estimated dependent variable score, c = constant, b = regression coefficient, and x = score on the independent variable.

Detailed explanation-2: -Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable’s value is called the independent variable.

Detailed explanation-3: -If you don’t select the correct model, you have made a specification error, which can invalidate your results. Specification error is when the independent variables and their functional form (i.e., curvature and interactions) inaccurately portray the real relationship present in the data.

Detailed explanation-4: -In regression analysis, a dummy variable (also known as indicator variable or just dummy) is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome.