With reference to your estimated equation, calculate (using a calculator) a 90% confidence interval for the coefficient of X (i.e.β2 ) in the model. In performing this calculation, use the relevant estimated standard error of the estimator of the coefficient of X given in your summary Excel regression output. Give an interpretation of the confidence interval you calculate. Regression Statistics Multiple R 0.319551492 R Square 0.102113156 Adjusted R Square 0.079665985 Standard Error 30180.01209 Observations 42 ANOVA df SS MS F Significance F Regression 1 4143419459 4.14E+09 4.549043 0.039125 Residual 40 36433325185 9.11E+08 Total 41 40576744644 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 102590.3493 11164.94377 9.188613 2.09E-11 80025.16 125155.5 80025.16 125155.5 X Variable 1 3592.882724 1684.546487 2.132849 0.039125 188.2873 6997.478 188.2873 6997.478 Marketer Hours of Training Sales Revenue 1 3 147643 2 6 120253 3 4 88777 4 3 157183 5 8 166802 6 2 127011 7 2 140582 8 10 104909 9 5 109778 10 5 110944 11 8 117820 12 3 136171 13 9 132366 14 5 64333 15 3 79541 16 7 179653 17 12 127204 18 6 114559 19 4 139737 20 4 71936 21 8 143105 22 6 158422 23 9 124784 24 10 151596 25 4 95001 26 3 103926 27 12 204264 28 9 213471 29 5 82178 30 7 123313 31 6 116686 32 3 126791 33 8 96543 34 6 136833 35 7 115203 36 3 108528 37 11 124951 38 10 98837 39 5 100181 40 5 102495 41 3 118540 42 4 134944
With reference to your estimated equation, calculate (using a calculator) a 90% confidence interval for the coefficient of X (i.e.β2 ) in the model. In performing this calculation, use the relevant estimated standard error of the estimator of the coefficient of X given in your summary Excel regression output. Give an interpretation of the confidence interval you calculate. Regression Statistics Multiple R 0.319551492 R Square 0.102113156 Adjusted R Square 0.079665985 Standard Error 30180.01209 Observations 42 ANOVA df SS MS F Significance F Regression 1 4143419459 4.14E+09 4.549043 0.039125 Residual 40 36433325185 9.11E+08 Total 41 40576744644 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 102590.3493 11164.94377 9.188613 2.09E-11 80025.16 125155.5 80025.16 125155.5 X Variable 1 3592.882724 1684.546487 2.132849 0.039125 188.2873 6997.478 188.2873 6997.478 Marketer Hours of Training Sales Revenue 1 3 147643 2 6 120253 3 4 88777 4 3 157183 5 8 166802 6 2 127011 7 2 140582 8 10 104909 9 5 109778 10 5 110944 11 8 117820 12 3 136171 13 9 132366 14 5 64333 15 3 79541 16 7 179653 17 12 127204 18 6 114559 19 4 139737 20 4 71936 21 8 143105 22 6 158422 23 9 124784 24 10 151596 25 4 95001 26 3 103926 27 12 204264 28 9 213471 29 5 82178 30 7 123313 31 6 116686 32 3 126791 33 8 96543 34 6 136833 35 7 115203 36 3 108528 37 11 124951 38 10 98837 39 5 100181 40 5 102495 41 3 118540 42 4 134944
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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- With reference to your estimated equation, calculate (using a calculator) a 90% confidence interval for the coefficient of X (i.e.β2 ) in the model. In performing this calculation, use the relevant estimated standard error of the estimator of the coefficient of X given in your summary Excel regression output. Give an interpretation of the confidence interval you calculate.
|
||||||||
Regression Statistics | ||||||||
Multiple R | 0.319551492 | |||||||
R Square | 0.102113156 | |||||||
Adjusted R Square | 0.079665985 | |||||||
Standard Error | 30180.01209 | |||||||
Observations | 42 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 1 | 4143419459 | 4.14E+09 | 4.549043 | 0.039125 | |||
Residual | 40 | 36433325185 | 9.11E+08 | |||||
Total | 41 | 40576744644 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | 102590.3493 | 11164.94377 | 9.188613 | 2.09E-11 | 80025.16 | 125155.5 | 80025.16 | 125155.5 |
X Variable 1 | 3592.882724 | 1684.546487 | 2.132849 | 0.039125 | 188.2873 | 6997.478 | 188.2873 | 6997.478 |
Marketer | Hours of Training | Sales Revenue |
1 | 3 | 147643 |
2 | 6 | 120253 |
3 | 4 | 88777 |
4 | 3 | 157183 |
5 | 8 | 166802 |
6 | 2 | 127011 |
7 | 2 | 140582 |
8 | 10 | 104909 |
9 | 5 | 109778 |
10 | 5 | 110944 |
11 | 8 | 117820 |
12 | 3 | 136171 |
13 | 9 | 132366 |
14 | 5 | 64333 |
15 | 3 | 79541 |
16 | 7 | 179653 |
17 | 12 | 127204 |
18 | 6 | 114559 |
19 | 4 | 139737 |
20 | 4 | 71936 |
21 | 8 | 143105 |
22 | 6 | 158422 |
23 | 9 | 124784 |
24 | 10 | 151596 |
25 | 4 | 95001 |
26 | 3 | 103926 |
27 | 12 | 204264 |
28 | 9 | 213471 |
29 | 5 | 82178 |
30 | 7 | 123313 |
31 | 6 | 116686 |
32 | 3 | 126791 |
33 | 8 | 96543 |
34 | 6 | 136833 |
35 | 7 | 115203 |
36 | 3 | 108528 |
37 | 11 | 124951 |
38 | 10 | 98837 |
39 | 5 | 100181 |
40 | 5 | 102495 |
41 | 3 | 118540 |
42 | 4 | 134944 |
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