Write a minimum 4 page report explaining the results from your analysis of the ROI of Business Majors and Engineering Majors. Use your results from each week’s assignment to make this report.This report should include:A detailed description of the data used in this analysis – specifically explain what the data in each column represents.A detailed explanation of any information learned about:School Type for each major; The Cost for each major;The 30 Year ROI for each major;The Annual % ROI for each major.Explanations should be supported with the results obtained from your work in previous weeks.Finally, answer the following questions and support your answer with your results.Does there appear to be a particular major that gives a better ROI? Why or Why not? Given that we are using statistical inference to make our conclusions, is it guaranteed that the major you choose that gave a better ROI for this sample will always have a better ROI than the other major? Explain your reasoningDOCUMENTS BELOW TO ANALYZE

Assignment ContentPurpose This assignment provides an opportunity to develop, evaluate, and apply bivariate and multivariate linear regression models.Resources: Microsoft Excel®, DAT565_v3_Wk5_Data_FileInstructions: 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 spaceOffices: number of offices in the buildingEntrances: number of customer entrancesAge: 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.Use Excel’s Analysis ToolPak to conduct a regression analysis with AssessmentValue as the dependent variable and FloorArea, Offices, Entrances, and Age as independent variables. What is the overall fit r^2? What is the adjusted r^2?Which predictors are considered significant if we work with α=0.05? Which predictors can be eliminated?What is the final model if we only use FloorArea and Offices as predictors?Suppose our final model is:AssessedValue = 115.9 + 0.26 x FloorArea + 78.34 x OfficesWhat wouldbe the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago? Is this asses