HWK
Please due on Sunday 12, Thanks!
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Please see the attachment for solution (Second Part 1-7)
body preview (39 words)
xxxxxx see the xxxxxxxxxx for xxxxxxxxx xx you need xxx xxxxxxxxxxxxx please xxxxxxx xxx xxxxxx leave x x star xxxxxx xx you are xxxxxxxxx xxxx my solution. The xxxx xxxx xxxxxxxx xxx xxxxxxxx and xxxxx file xxxxxxxx the computations.
file1.doc preview (1922 words)
For the data xxx shown xxxxxx do xxxx following. xxx xxxxxxx xxx standard error the xxxxx estimate for xxx (b) Assuming the residuals are normally distributed, xxxxxxxxx Sb1. (c) Assuming the residuals xxx normally xxxxxxxxxxxx xxxx H0;β1=0 xxxxxx xxx β1≠x at the xxxxxx xxxxx xx xxxxxxxxxxxxx xxx null xxxxxxxxxx is that x xxx y are xxx linearly related.
X 3 x x x 8
Y x 6 8 13 15
xxxxxxxxx xxx xxxxx xxxxxxxx for xxx Se ≈ (xxxxxxxxxx xxx round xxxxx the xxxxx answer. Then xxxxx to four xxxxxxx xxxxxx xx xxxxxxxx
Recall that b1 is xxx xxxxxxxx xx xxxxx of the regression xxxx xxxx The sample xxxxxxxx error xx xx xx given by xxx xxxxxxxxx xxxxxxxxx
In xxxxx xx conduct xxx hypothesis test, first xxxxxxxxx the xxxx statistic t0.(Explain the xxxxxxx
- - - more text follows - - -
file2.xls preview (378 words)
xx
| X | xY | xY^ | xxxxxxxxxx | x(Residual)^2 | (X-Xbar)^2 |
| x | xx | xxxxxxx | x0.6512 | x0.4240 | xxxxx |
| x | xx | 6.4535 | x-0.4535 | x0.2057 | xxxxx |
| x | 8 | xxxxxx | xxxxxxxx | 0.3115 | xxxxx |
| 7 | xxx | xxxxxxxx | x0.2326 | xxxxxxx | 2.56 |
| x | 15 | x14.8721 | x0.1279 | xxxxxxx | xxxx |
| xxx | xxxxxx | xxxxxxx | |||
| Xbar | xxx | ||||
| xxxxxx xx x | 2.1047 | ||||
| Intercept, bo = | xxxxxxxx | ||||
| x x | x | ||||
| Se = | xxxxxxx | ||||
| Sb1 | x0.1400 | ||||
| x x xxxxxx = | xxxxxxxxxxxxx | ||||
| xxxxxxx x | 0.0006 |
Q2
| X | Y | xx | xResiduals | x(Residual)^2 | xxxxxxxxxxx |
| xx | x98 | xxxxxxxx | xxxxxxxx | xxxxxxxx | xxx |
| xx | x95 | xxxxxxxx | x1.0000 | xxxxxx | x100 |
| 40 | x91 | xxxxxxxx | xxxxxxx | xxxxxxx | x0 |
| xx | 81 | 79.2000 | xxxxxxx | 3.2400 | 100 |
| xx | xxx | 71.8000 | xxxxxxxx | xxxxxxxx | 400 |
| xxx | x49.6000 | 1000.0000 | |||
| xxxx | x40 | ||||
| Slope, b1 x | xxxxxxx | ||||
| Intercept, xx x | xxxxxxxx | ||||
| x x | 5 | ||||
| Se x | 4.0661 | ||||
| Sb1 | xxxxxxx | ||||
| x x b1/Sb1 x | xxxxxxx | ||||
| xxxxxxx x | xxxxxxx |
xx
| x | Y | xx | xxxxxxxxx | (Residual)^2 | xxxxxxxxxxx | ||
| 3330 | xxxxx | xxxxxxxxxx | -49.7239 | xxxxxxxxx | xxxxxx | ||
| 2620 | xxxxx | x4271.1728 | xxxxxxxxx | xxxxxxxxxx | 40804 | ||
| 3380 | x5020 | x4943.9881 | xxxxxxxx | xxxxxxxxx | x311364 | ||
| xxxx | xxxxx | xxxxxxxxx | 82.1179 | xxxxxxxxxx | xxxxxxx | ||
| xxxx | 4120 | 4147.2331 | -27.2331 | xxxxxxxxx | x116964 | ||
| Sum | x22324.2878 | 999680.0000 | |||||
| xxxx | 2822 | ||||||
| Slope, b1 x | xxxxxxx | ||||||
| xxxxxxxxxx xx x | xxxxxxxxx | ||||||
| n = | x | ||||||
| Se = | 86.2637 | ||||||
| Sb1 | xxxxxxx | ||||||
| x = xxxxxx x | 10.2609 | ||||||
| P-value x | xxxxxxx | ||||||
| Confidence xxxxxxxx | |||||||
| t(a/2) x | 3.182 | ||||||
| xxxxx limit x | x0.611 | ||||||
| upper xxxxx x | 1.160 | ||||||
| Forecast x | xxxxxxx | ||||||
| xxxxxxx xxxxxx | |||||||
| Regression Statistics | |||||||
| xxxxxxxx x | x0.9861 | ||||||
| R Square | 0.9723 | ||||||
| xxxxxxxx R xxxxxx | xxxxxx | ||||||
| xxxxxxxx xxxxx | xxxxxxxx | ||||||
| Observations | xx | ||||||
| xxxxx | |||||||
| xx | xSS | MS | xx | Significance x | |||
| xxxxxxxxxx | xx | x783475.712227913 | x783475.712227913 | 105.2856 | 0.0020 | ||
| xxxxxxxx | xx | xxxxxxxxxxxxxxxx | 7441.4292573624 | ||||
| xxxxx | 4 | xxxxxx | |||||
| Coefficients | xxxxxxxx xxxxx | t Stat | xxxxxxxx | Lower 95% | Upper 95% | xLower xxxxx | xxxxxx - - - more text follows - - - |
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on Sun, 2012-08-12 00:24