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I have a quantitative term project due using simple linear regression. I have the data in excel however the requirements are a 4-model table evaluation.

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I have a quantitative term project due using simple linear regression. I have the data in excel however the requirements are a 4-model table evaluation. I'm having trouble identifying the equations used for the different models. I included the project and data

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A B C D G H 1 Quantitative Project Data 2 Spring 2021 4 PCONS = Personal Consumption Expenditures (Seasonally Adjusted, $ billions) 5 DPI = Disposable Personal Income (Seasonally Adjusted, $ billions) 6 TREND = Trend or Observation 7 8 g 10 Year Quarter PCONS DPI TREND 11 1981 2 1831.874 2125.848 H 12 1981 3 1885.734 2177.992 2 13 1981 4 1917.524 2217.133 3 14 1982 1 1958.099 2302.221 15 1982 2 1974.447 2339.999 16 1982 3 2014.155 2375.323 6 17 1982 4 2039.645 2412.547 7 18 1983 1 2085.671 2462.319 19 1983 2 2145.554 2497.228 9 20 1983 3 2184.589 2541.526 10 21 1983 4 2249.438 2582.521 11 22 1984 1 2319.895 2655.754 12 23 1984 2 2372.496 2732.912 13 24 1984 3 2418.165 2817.775 14 25 1984 4 2475.876 2892.421 15 26 1985 1 2513.523 2953.265 16 27 1985 2 2561.797 2995.748 17 28 1985 3 2636.008 3023.121 18 29 1985 4 2681.764 3106.975 19 30 1986 1 2754.148 3121.548 20 31 1986 2 2779.400 3176.623 21 32 1986 3 2823.648 3241.309 22 33 1986 2851.456 3279.358 23 34 1987 2917.201 3317.667 24 35 1987 2 2952.807 3342.776 25 Sheet1SUMMARY OUTPUT Regression Statistics Multiple R 0.997812484 R Square 0.995629754 Adjusted R Square 0.995574082 Standard Error 254.8521474 Observations 160 ANOVA df SS MS F Significance F Regression 2 2323101687 1161550844 17883.87517 6.0216E-186 Residual 157 10197089.88 64949.61704 Total 159 2333298777 Coefficients |Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 211.2603393 45.98165503 4.594448354 8.85769E-06 120.4378726 302.082806 120.4378726 302.082806 DPI 0.628601593 0.029655657 21.19668377 6.37686E-48 0.57002606 0.687177126 0.57002606 0.687177126 TREND 24.18224952 2.761411331 8.757206594 3.01922E-15 18.72793978 29.63655925 18.72793978 29.63655925Table of Contents > Term Project > ECON 222 Quantitative Project Discussion ECON 222 Quantitative Project Discussion PCONS = 10 + 0.8 DPI R= . 9400 Fit+ ( . 02 ) 2 pv. Ine PLONS = 8+ 0.75DDI+ 7TREND R = 9502 (, 02 ) ( . 04 ) P LON S = 5 + 0. 9 9 SQ DI I R *= 9450 ( . 01 ) P LON S = 5+ 0. 85 5 Q DPI + 5TREND R 2- 9600 ( . 01 ) (. 60 ) 10:56 / 29:36ECON 222 Quantitative Project Discussion ~

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