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eco_500_excel_assignment_one.xls 

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ECO 500: Excel Assignment One Below are data for U.S. DPI and PCE on two major components of consumer spending, motor vehicles and parts and housing and utilities. One is a durable good and the other is comprised of housing and other services and non-durables, such as natural gas purchases. Using scatter diagrams and trendlines, generate graphs showing the relationship of each of the consumption categories to DPI and find the equation of the graph and the R squared. Use your results to answer the questions to the right. Data Year Motor Vehicles and Parts DPI 1964. 462.3 25.8 1965. 497.8 29.6 1966. 537.4 29.9 1967. 575.1 29.6 1968. 624.7 35.4 1969. 673.8 37.4 1970. 735.5 34.5 1971. 801.4 43.2 1972. 869.0 49.4 1973. 978.1 54.4 1974. 1,071.7 48.2 1975. 1,187.3 52.6 1976. 1,302.3 68.2 1977. 1,435.0 79.8 1978. 1,607.3 89.2 1979. 1,790.9 90.2 1980. 2,002.7 84.4 1981. 2,237.1 93.0 1982. 2,412.7 100.0 1983. 2,599.8 122.9 1984. 2,891.5 147.2 1985. 3,079.3 170.1 1986. 3,258.8 187.5 1987. 3,435.3 188.2 1988. 3,726.3 202.2 1989. 3,991.4 207.8 1990. 4,254.0 205.1 1991. 4,444.9 185.7 1992. 4,736.7 204.8 1993. 4,921.6 224.7 Questions: a) Plot the data using a scatterplot. b) Find the equation that shows the rela c) Find the equation that shows the rela d) What are the R squares for the equati e) Use the equations to calculate estima f) If DPI increases at a rate of 2.2% in 20 Answers: a) b) c) d) e) f) Motor Vehicles and Parts 2013 2014 Housing and Utilities 2013 2014 1994. 5,184.3 249.8 1995. 5,457.0 255.7 1996. 5,759.6 273.5 1997. 6,074.6 293.1 1998. 6,498.9 320.2 1999. 6,803.3 350.7 2000. 7,327.2 363.2 2001. 7,648.5 383.3 2002. 8,009.7 401.3 2003. 8,377.8 401.0 2004. 8,889.4 403.9 2005. 9,277.3 408.2 2006. 9,915.7 394.8 2007. 10,423.6 399.9 2008. 11,024.5 339.3 2009. 10,722.4 316.0 2010. 11,127.1 342.7 2011. 11,549.3 373.6 11,931.2 407.0 p 2012 . Year Housing and Utilities DPI 1964. 462.3 72.1 1965. 497.8 76.6 1966. 537.4 81.2 1967. 575.1 86.3 1968. 624.7 92.7 1969. 673.8 101.0 1970. 735.5 109.4 1971. 801.4 120.0 1972. 869.0 131.2 1973. 978.1 143.5 1974. 1,071.7 158.6 1975. 1,187.3 176.5 1976. 1,302.3 194.7 1977. 1,435.0 217.8 1978. 1,607.3 244.3 1979. 1,790.9 273.4 1980. 2,002.7 311.8 1981. 2,237.1 352.0 1982. 2,412.7 387.0 1983. 2,599.8 421.2 1984. 2,891.5 458.3 1985. 3,079.3 500.7 1986. 3,258.8 535.7 1987. 3,435.3 571.8 1988. 3,726.3 614.5 1989. 3,991.4 655.6 1990. 4,254.0 696.4 1991. 4,444.9 735.5 1992. 4,736.7 771.2 1993. 4,921.6 814.5 1994. 5,184.3 866.5 1995. 5,457.0 913.8 1996. 5,759.6 961.2 1997. 6,074.6 1,009.9 1998. 6,498.9 1,065.2 1999. 6,803.3 1,125.0 2000. 7,327.2 1,198.6 2001. 7,648.5 1,287.7 2002. 8,009.7 1,334.8 2003. 8,377.8 1,393.9 2004. 8,889.4 1,462.4 2005. 9,277.3 1,582.6 2006. 9,915.7 1,686.2 2007. 10,423.6 1,756.2 2008. 11,024.5 1,831.0 2009. 10,722.4 1,871.6 2010. 11,127.1 1,891.9 2011. 11,549.3 1,929.9 11,931.2 1,965.9 p 2012 . Source: Economic Report of the President, 2013. Appendix B. ta using a scatterplot. uation that shows the relationship between motor vehicles and parts expenditure (PCE) and DPI (insert a linear trendline and show the e uation that shows the relationship between housing and utilities expenditures (PCE) and DPI (insert a linear trendline and show the equa he R squares for the equations? Which one is better? Can you provide an economic rationale to explain the difference? uations to calculate estimated values for both types of expenditures for 2011 and 2012. How well did the equations predict values for 201 ases at a rate of 2.2% in 2013 and then at a rate of 2.6% in 2014, what are the predicted values for consumer spending on motor vehicles Vehicles and Parts sing and Utilities
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