Stepwise_Regression

Stepwise Regression VII. Stepwise Regression One approach to finding the regression model is called stepwise regression which attempts to find the best regression model without examining the regression of all possible variables. After the best model has been determined, residual analysis is used to evaluate the appropriateness of the model. In this particular model, appraised value is the dependent variable and the independent variables include, lot size, number of bedrooms, number of rooms, age of home, central air-conditioning, fireplace, connection to local sewer system, basement, and taxes paid. 1) At the first step, the regression equation is as follows: Appraised Value = 101.928 + .03402 Taxes R-Squared = 0.627 For each increase in taxes paid by one dollar, there is an expected increase in appraised value by $34.02. It can also be concluded that 62.7% of the total variation in appraised value can be explained by the variation in taxes paid and 37.3% is the remaining unexplained variation. The reason why taxes paid is the independent variable in step one is because taxes have the highest correlation with value, thus, taxes will be the first variable to be chosen to predict appraised value when stepwise regression model is value, taxes, appraised, regression, variables, rooms, age, paid, model, number, cac, one, significant, house, stepwise, reject, null, level, hypothesis, equal, alpha, hi, variation, variable, taking, provide, presence, information, increase, graph, estimated, consideration, conclude, bj