Regression analysis is a statistical tool used for the examination of relationships between variables. Linear regression analysis is used to estimate the strength and the direction of the relationship between two linearly related variables.

Explain the differences between the regression model, the regression equation, and the estimated-regression equation. Discuss the application of regression analysis in business decision making. Give examples on how the regression analysis can be used in business.

Question 25 Simple Regression analysis and Mumvariate Regression Analysis me raised to each other in ihn following way; @) Both techniques use a goodness of fit musmire, but the goodness of fit meamie in Muhivanale Regression adjusts Nu the fact that an coun miinhis aduspammin Ingphompants Simple Regression is simpler than Multivariate Regression because the dependent variable is aways a straight line function of the independent sunable un a graph Multivariate regression always proves causation, but simple regression can never prove causation Both simple and multiple regression face the problem of multicollinearityA Y = Ar 4 By 4 0x 1 - Applying the state space theories to determine the transition matrix & this system. show steps in detail.2 0 A fundamental basis of regression analysis is the assumption of: Multiple Choice Skipped O the existence of two independent variables for every dependent variable. the lack of a relationship between independent variables. a straight line relation ship between the in dependent and dependent variables. a uniform normal distribution between dependent variables. a curvilinear relationship between two weakly associated dependent variables. OOOO