THE QUESTION: Is this regression model significant? What tells you this? What do
ID: 3055082 • Letter: T
Question
THE QUESTION: Is this regression model significant? What tells you this?
What do the residual plots tell us? Are there any regression violations?
Interpret the meaning of the Intercept in your coefficient table below.
RESIDUAL OUTPUT Observation Predicted Y Residuals 1 680.4140911 -100.4140911 2 923.8811668 -224.8811668 3 702.7377198 7.262280216 4 729.2470289 -9.247028889 5 649.7191016 79.28089842 6 623.9074059 115.0925941 7 1156.186428 -407.1864282 8 642.7429676 116.2570324 9 784.3584873 -18.35848729 10 824.8200643 -19.82006434 11 777.3823533 72.61764668 12 759.9420184 109.0579816 13 835.2842653 34.71573469 14 804.5892758 67.41072418 15 809.4725696 64.5274304 16 765.5229256 109.4770744 17 923.8811668 -23.88116679 18 934.3453677 -14.34536775 19 1023.639883 -89.63988263 20 943.4143419 -4.414341917 21 857.607894 82.39210597 22 1049.451578 -104.4515783 23 1044.568285 -84.56828455 24 993.6425065 -18.64250654 25 1160.372109 -185.3721085 26 993.6425065 1.357493464 27 1018.058975 -18.05897545 28 1142.23416 -122.2341602 29 978.2950118 41.70498821 30 1067.589527 -47.58952667 31 1021.547042 8.452957564 32 1084.332248 -39.33224821 33 1272.687866 -223.6878655 34 1077.356114 -27.35611423 35 1119.212918 -69.21291808 36 1286.640133 -236.6401335 37 1481.971885 -401.9718848 38 1161.069722 -52.06972193 39 1084.332248 25.66775179 40 1140.14132 -15.14132001 41 1133.165186 -4.165186034 42 1119.212918 19.78708192 43 1179.905284 -24.90528367 44 1147.117454 12.88254602 45 1292.221041 -122.2210407 46 1268.502185 -33.50218515 47 1137.350866 101.6491336 48 1447.091215 -197.0912149 49 1468.019617 -218.0196168 50 1258.735598 11.26440242 51 1860.77596 -561.7759596 52 1518.945395 -168.9453948 53 1228.738221 146.2617785 54 1140.14132 308.85868 55 1481.971885 71.02811522 56 1286.640133 273.3598665 57 1991.927278 -296.9272783 58 1882.401975 -82.40197493 59 1516.852555 327.1474453 60 1747.064976 152.9350242 61 1747.064976 251.9350242 62 1795.897914 254.1020864 63 1423.372359 676.6276406 64 1805.664501 344.3354988 65 1934.025366 215.9746337 66 1984.951144 165.0488556 Get &Trarsferm; eta Oueries Connecticrs Sort&Hike; Uata Tocl Analysis Chart 1-Xf A. 1 SUJMMARY OLUTPLUT X Variable 1 Residual Plot 4 Multiple R 5 RSquare 0.88394183 0.781353159 6 Adjusted R Squa.777936802 190.5561G07 7 Standard Error Observations 10 ANOVA MS Significoncef 12 Regression 13 Residual 4 Total 130421 1348304818.134 2323945.624 36311.65037 10628763.76 22B.7094651 8.330B6E-23 Variable 1 Stondard Error tStor valuc ver 95% Upper 95% Lower 95.0% Uppcr 95.0% 17 Intercept 18 XVariable 1 52.77758969 0.697613397 84.09974023 -0.627559485 0.046128862 15.12314336 0.532525314 220.7861347 0.605460401 115.2309S53220.7861347 115.2309553 .789766391 B.33086E-23 0.605460101 0.789766394 20 21 22 RESIDUAL OUTPU Predicted y 25 1 680.4140911 100.4140911 224.8811668 /.26228U216 9.247028889 79.28089842 2 923.8811668 27 28 4 729.2470289 5 649.7191016Explanation / Answer
Is this regression model significant? What tells you this?
Interpret the meaning of the Intercept in your coefficient table below.
The p-value of F test is 0.0000
Since this p-value is zero so model is significant.
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What do the residual plots tell us?
Resildual plot does not show any specific pattern. It is football shaped. So it seems to be good fit.
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Are there any regression violations?
No, it seems to be a good fit.
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Interpret the meaning of the Intercept in your coefficient table below.
The intercept is : -52.776
It shows that when X=0, then predcited value of Y is -52.776.
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