Lab 5 - OLS Live and Regression

Lab 5 - OLS Live and Regression - 0.30 50 100 150 200 250...

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Obs. Y X x y x*y xsq 1 70 80 2 95 100 3 90 120 4 105 140 5 140 160 6 135 180 7 130 200 8 170 220 9 160 240 10 180 260 Totals 1275 1700 Means: 127.5 170 St. Dev: 36.69 60.55 beta 1 hat beta 0 hat
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Table 1: Generating the sum of the squared errors. Y X e 70 80 100.85 -30.85 951.63 95 100 118.85 -23.85 568.75 90 120 136.85 -46.85 2194.78 105 140 154.85 -49.85 2484.87 140 160 172.85 -32.85 1079.02 135 180 190.85 -55.85 3119.05 130 200 208.85 -78.85 6217.08 170 220 226.85 -56.85 3231.75 160 240 244.85 -84.85 7199.27 180 260 262.85 -82.85 6863.87 Totals -543.48 33910.08 28.85 0.90 33910.08 0.9 0.80 0.70 0.60 0.50 0.40
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Unformatted text preview: 0.30 50 100 150 200 250 300 50 100 150 200 250 OLS: Finding the line of "best fit." X Y 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 5000 10000 15000 20000 25000 30000 35000 40000 Plotting the Sum of Squared Errors Slope Estimates Enter values here for the intercept and slope of the fitted line. OLS grap 1 ˆ β 1 ˆ ˆ 2 i e ∑ 2 i e ˆ i Y Live: What's happening in the table and these phs?...
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This note was uploaded on 12/08/2011 for the course ECON 312 taught by Professor Daniellass during the Winter '10 term at UMass (Amherst).

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Lab 5 - OLS Live and Regression - 0.30 50 100 150 200 250...

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