Bivariate and multivariate linear regression models.

Develop, evaluate, and apply bivariate and multivariate linear regression models. The Excel file for this assignment contains a database with information about the tax assessment value assigned to medical office buildings in a city. The following is a list of the variables in the database: FloorArea: square feet of floor space Offices: number of offices in the building Entrances: number of customer entrances Age: age of the building (years) AssessedValue: tax assessment value (thousands of dollars) Use the data to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics. Construct a scatter plot in Excel with FloorArea as the independent variable and AssessmentValue as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables? Use Excel’s Analysis ToolPak to conduct a regression analysis of FloorArea and AssessmentValue. Is FloorArea a significant predictor of AssessmentValue? Construct a scatter plot in Excel with Age as the independent variable and AssessmentValue as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables? Use Excel’s Analysis ToolPak to conduct a regression analysis of Age and Assessment Value. Is Age a significant predictor of AssessmentValue? Construct a multiple regression model.