The above datafile (in the "Data" worksheet) provides the market historical data set of real estate valuation collected from Sindian Dist, New Taipei City, Taiwan. The data set come up with house price of unit area based on the six different corresponding fields including (transaction date, house age, distance to the nearest MRT station, number of convenience store in the living circle on foot, geographic coordinate, latitude and geographic coordinate, longitude. The description inputs variables is provided in the "Description" worksheet. a. Develop an estimated multiple linear regression equation that relates the house price of unit area to the transaction date, house age, distance to the nearest MRT station, number of convenience store in the living circle on foot, geographic coordinate, latitude and geographic coordinate, longitude. b. According to the results in (a), use the F test to determine the overall significance of the regression relationship and give overall conclusion at the 0.01 level of significance. c. Determine the significance of each independent variable using the t test and give the conclusion for each test at the 0.01 level of significance. d. Choosing significant at the 0.01 level of significance, perform additional relevant analysis for the signifant inputs towards the house price of unit area. e. What is your final recommended estimated regression equation? Explain your reasons. The inputs are as follows: X1= the transaction date (for example, 2013.250=2013 March, 2013.500=2013 June, etc.) X2= the house age (unit: year) X3-the distance to the nearest MRT station (unit: meter) X4= the number of convenience stores in the living circle on foot (integer) X5= the geographic coordinate, latitude. (unit: degree) X6=the geographic coordinate, longitude. (unit: degree) The output is as follow The above datafile (in the "Data" worksheet) provides the market historical data set of real estate valuation collected from Sindian Dist, New Taipei City, Taiwan. The data set come up with house price of unit area based on the six different corresponding fields including (transaction date, house age, distance to the nearest MRT station, number of convenience store in the living circle on foot, geographic coordinate, latitude and geographic coordinate, longitude. The description inputs variables is provided in the "Description" worksheet. a. Develop an estimated multiple linear regression equation that relates the house price of unit area to the transaction date, house age, distance to the nearest MRT station, number of convenience store in the living circle on foot, geographic coordinate, latitude and geographic coordinate, longitude. b. According to the results in (a), use the F test to determine the overall significance of the regression relationship and give overall conclusion at the 0.01 level of significance. c. Determine the significance of each independent variable using the t test and give the conclusion for each test at the 0.01 level of significance. d. Choosing significant at the 0.01 level of significance, perform additional relevant analysis for the signifant inputs towards the house price of unit area. e. What is your final recommended estimated regression equation? Explain your reasons. The inputs are as follows: X1= the transaction date (for example, 2013.250=2013 March, 2013.500=2013 June, etc.) X2= the house age (unit: year) X3-the distance to the nearest MRT station (unit: meter) X4= the number of convenience stores in the living circle on foot (integer) X5= the geographic coordinate, latitude. (unit: degree) X6=the geographic coordinate, longitude. (unit: degree) The output is as follow
