Question

Given the data and output in the attached file, Construct a 90% confidence interval estimate for...

Given the data and output in the attached file, Construct a 90% confidence interval estimate for the average Sales when Advertising is 25 want a confidence interval. It uses Regressionquizoutput2. Regressionquizoutput1 Regression Statistics Multiple R R Square Adjusted R Square Standard Error N Observations 6 ANOVA df SS MS Regression 1 0.607903685 0.607903685 Residual 4 0.020846315 0.005211579 Total 5 0.62875 Coefficients Standard Error Intercept 1.799069984 0.153403661 GMAT 0.002912113 0.000269635 A graduate school wants to try to predict GPA based on GMAT score. A random sample of 6 students was selected. The data was place into Excel. Partial regression output is shown above.

Homework Answers

Answer #1

the first sentence of the question is not a part of the regresion output given , as regression output is for gpa and gmat

we can for the regression equation as

gpa = 1.799 + 0.0029*GMAT

so if we have to predict the GPA , we can put the value of GMAT in the above equation and solve it

lets say gmat = 600

so gpa would be


gpa = 1.799 + 0.0029*600 = 3.53

also , note that confidence interval is given as

point +- z*sd/sqrt(n)

sd/sqrt(n) is also called Standard error

so if were to form 90% CI for GMAT coefficient it would be
z = 1.645 for 90% CI from the z table


0.002912113 +- 1.645*0.000269635
solving for plus and minus signs we get

= 0.00246 and 0.0033

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
] A partial computer output from a regression analysis using Excel’s Regression tool follows. Regression Statistics...
] A partial computer output from a regression analysis using Excel’s Regression tool follows. Regression Statistics Multiple R (1) R Square 0.923 Adjusted R Square (2) Standard Error 3.35 Observations ANOVA df SS MS F Significance F Regression (3) 1612 (7) (9) Residual 12 (5) (8) Total (4) (6) Coefficients Standard Error t Stat P-value Intercept 8.103 2.667 x1 7.602 2.105 (10) x2 3.111 0.613 (11)
Using the attached regression output, answer the following: SUMMARY OUTPUT Regression Statistics Multiple R 0.972971 R...
Using the attached regression output, answer the following: SUMMARY OUTPUT Regression Statistics Multiple R 0.972971 R Square 0.946673 Adjusted R Square 0.944355 Standard Error 76.07265 Observations 49 ANOVA df SS MS F Significance F Regression 2 4725757 2362878 408.3046 5.24E-30 Residual 46 266204.2 5787.049 Total 48 4991961 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -0.46627 14.97924 -0.03113 0.975302 -30.6179 29.68537 X1 0.09548 0.084947 1.123997 0.266846 -0.07551 0.26647 X2 0.896042 0.205319 4.364141 7.16E-05 0.482756 1.309328 a. What...
Below you are given a partial Excel output based on a sample of 16 observations. ANOVA...
Below you are given a partial Excel output based on a sample of 16 observations. ANOVA df SS MS F Regression 4,853 2,426.5 Residual 485.3 Coefficients Standard Error Intercept 12.924 4.425 x1 -3.682 2.630 x2 45.216 12.560 ? ? Refer to Exhibit 13-6. Carry out the test of significance for the parameter ?1 at the 1% level. The null hypothesis should be Select one: a. None of these alternatives is correct. b. revised c. rejected d. not rejected
According to the Data, is the regression a better fit than the one with the Dummy...
According to the Data, is the regression a better fit than the one with the Dummy variable, explain? Regression Statistics Multiple R 0.550554268 R Square 0.303110002 Adjusted R Square 0.288887757 Standard Error 2.409611727 Observations 51 ANOVA df SS MS F Significance F Regression 1 123.7445988 123.7445988 21.31238807 2.8414E-05 Residual 49 284.5052051 5.806228676 Total 50 408.2498039 Coefficients Standard Error t Stat P-value Lower 95% Intercept 5.649982553 1.521266701 3.713998702 0.000522686 2.592882662 U-rate 1.826625993 0.395670412 4.616534206 2.84144E-05 1.0314965 Multiple R 0.572568188 R Square...
Multiple R=0.81112189 R Square=0.65791872 Adj. R Square=0.61515856 Standard Error=11.6506589 Observations=10 Regression: df=1 ss=2088.497175 ms=2088.497 F=15.3863 Residual:...
Multiple R=0.81112189 R Square=0.65791872 Adj. R Square=0.61515856 Standard Error=11.6506589 Observations=10 Regression: df=1 ss=2088.497175 ms=2088.497 F=15.3863 Residual: df=8 ss=1085.902825 ms=135.7379 Total: df=9 ss=3174.4 Intercept: Coefficients=-70.39 Std. Error=30.00 P-value=0.047 X: Coefficients=17.18 Std. Error=4.38 t-stat=3.92 p value=0.004 Question: For the test of hypothesis regarding the intercept of the model, compute and report the calculated value of the test-statistic. Question: Predict value of Y, when X = 10.
True or false: at the 5% level of confidence the intercept is significantly different from zero?...
True or false: at the 5% level of confidence the intercept is significantly different from zero? SUMMARY OUTPUT Regression Statistics Multiple R 0.98711 R Square 0.974387 Adjusted R Square 0.965849 Standard Error 47.4523 Observations 9 ANOVA df SS MS F Significance F Regression 2 513960.7 256980.4 114.1262 1.68E-05 Residual 6 13510.32 2251.72 Total 8 527471.1 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -100.805 48.43281 -2.08133 0.082583 -219.316 17.70612 -219.316 17.70612 Well Depth...
(a) Present the regression output below noting the coefficients, assessing the adequacy of the model and...
(a) Present the regression output below noting the coefficients, assessing the adequacy of the model and the p-value of the model and the coefficients individually. SUMMARY OUTPUT Regression Statistics Multiple R 0.19476248 R Square 0.037932424 Adjusted R Square 0.035147858 Standard Error 12.09940236 Observations 694 ANOVA df SS MS F Significance F Regression 2 3988.511973 1994.255986 13.62238235 1.5759E-06 Residual 691 101159.3165 146.3955376 Total 693 105147.8284 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 27.88762549...
SUMMARY OUTPUT Regression Statistics Multiple R 0.84508179 R Square 0.714163232 Adjusted R Square 0.704942691 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.84508179 R Square 0.714163232 Adjusted R Square 0.704942691 Standard Error 9.187149383 Observations 33 ANOVA df SS MS F Significance F Regression 1 6537.363661 6537.363661 77.4535073 6.17395E-10 Residual 31 2616.515127 84.40371378 Total 32 9153.878788 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 61.07492285 3.406335763 17.92980114 6.41286E-18 54.12765526 68.02219044 54.12765526 68.02219044 Time (Y) -0.038369095 0.004359744 -8.800767426 6.17395E-10 -0.047260852 -0.029477338 -0.047260852 -0.029477338 Using your highlighted cells, what is the equation...
Use Excel to develop a regression model for the Hospital Database (using the “Excel Databases.xls” file...
Use Excel to develop a regression model for the Hospital Database (using the “Excel Databases.xls” file on Blackboard) to predict the number of Personnel by the number of Births. Perform a test of the slope. What is the value of the test statistic? Write your answer as a number, round your answer to 2 decimal places. SUMMARY OUTPUT Regression Statistics Multiple R 0.697463374 R Square 0.486455158 Adjusted R Square 0.483861497 Standard Error 590.2581194 Observations 200 ANOVA df SS MS F...
Dep.= Mileage Indep.= Cylinders SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard...
Dep.= Mileage Indep.= Cylinders SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 7.0000 ANOVA Significance df SS MS F F Regression 12.4926 Residual Total 169.4286 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept 38.7857 Cylinders -2.7500 SE CI CI PI PI Predicted Predicted Lower Upper Lower Upper x0 Value Value 95% 95% 95% 95% 4.0000 1.9507 6.0000 1.1763 Is there a relationship between a car's gas MILEAGE (in miles/gallon) and its...