Multiple Linear Regression Models Applied to Urban Terrain Assessment - Municipality of Itaqui - RS Case

This work had as objective to identify explanatory variables for modeling and prediction of actual value (ITBI) and venal value of urban plot in the city of Itaqui-RS using the comparative method of Direct market data, developed by multiple linear regression. In a sample of 67 lots, quantitative variables were evaluated: area, front of urban plot, value of m(2), market value and the value ITBI and qualitative variables: topography, location and flooring, and for each variable were determined statistical parameters including the data distribution for asymmetry, kurtosis, normality test of Kolmogorov-Smirnov, as well as the Pearson linear correlation and path analysis, which shows the relationships of cause and effect of the explanatory variables on the market and ITBI values, respectively. The importance of each explanatory variable on the model of market and ITBI values was determined by the stepwise method. The market value showed a positive, significant correlation (p <= 0.05) and increased with flooring, front of urban plot, area and value of m(2), in that order. Already ITBI value was positively correlated, significant (p <= 0.05) and with increasing value of m(2) and flooring, in that order. Path analysis indicated that the area and the value of m(2) have cause and effect on the market value and, the value of m(2) and flooring shows cause and effect on the value of ITBI. The models: Y=16.90xarea + 594.69xvalue of m(2) - 9526.54xtopography (r(2)=0.91) and, Y=868.36xvalue of m(2) - 23642.19xtopography + 33633.46xflooring (r(2)=0.70), are suitable for the estimation of market and ITBI values, respectively.