A regression equation or a model is developed step by step.

the model to be developed should fall under one of the three categories either: forecasting, policy making or analysis of the model.

One should determine the explanatory (predictors) and Explained (Predicted) variables in a given data.

For instance, to develop the model of income of employees one has to have information concerning the income and salary from a sample. From there you can be able to determine autonomous income beside the salary and thereafter you can predict the income of employees using the model.

One should be careful when developing these models because some situation may occur where the explanatory is dependent of the predicted and vice verse hence, employing sophisticated technique like Indirect Least Square Estimates.

y= a + bx + e

When a model Have normal distribution, Zero mean, constant variance among the Explanatory and residual its homoscedastic and if the three assumption are violated hence heteroscedastic give a way to to our data is either Macro or Micro and call for the appropriate measures.

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A regression equation or a model is developed step by step.

the model to be developed should fall under one of the three categories either: forecasting, policy making or analysis of the model.

One should determine the explanatory (predictors) and Explained (Predicted) variables in a given data.

For instance, to develop the model of income of employees one has to have information concerning the income and salary from a sample. From there you can be able to determine autonomous income beside the salary and thereafter you can predict the income of employees using the model.

One should be careful when developing these models because some situation may occur where the explanatory is dependent of the predicted and vice verse hence, employing sophisticated technique like Indirect Least Square Estimates.

y= a + bx + e

When a model Have normal distribution, Zero mean, constant variance among the Explanatory and residual its homoscedastic and if the three assumption are violated hence heteroscedastic give a way to to our data is either Macro or Micro and call for the appropriate measures.