The number of pounds of steam used per month by a chemical plant is thought to be related to the average ambient temperature (in F) for that month. The past year’s usage and temperatures are in the following table: Month Temp. Usage/1000 Month Temp. Usage/1000 Jan. 21 185.79 July. 68 621.55 Feb. 24 214.47 Aug. 74 675.06 Mar. 32 288.03 Sept. 62 562.03 Apr. 47 424.84 Oct. 50 452.93 May 50 454.58 Nov. 41 369.95 June 59 539.03 Dec. 30 273.93 Assuming that a simple linear regression model is appropriate, fit the regression model relating stem usage (y) to the average temperature (x). What is the estimate of ? What is the estimate of expected stem usage when the average temperature is 55 F? What change in mean stem usage is expected when the monthly average temperature changes by 1 F? Suppose that the monthly average temperature is 47 F. Calculate the fitted value of y and the corresponding residual. Test for significance of regression using α=0.01 (Use ANOVA). Calculate the r2 of the model. Find a 99% CI for .
The number of pounds of steam used per month by a chemical plant is thought to be related to the average ambient temperature (in F) for that month. The past year’s usage and temperatures are in the following table: Month Temp. Usage/1000 Month Temp. Usage/1000 Jan. 21 185.79 July. 68 621.55 Feb. 24 214.47 Aug. 74 675.06 Mar. 32 288.03 Sept. 62 562.03 Apr. 47 424.84 Oct. 50 452.93 May 50 454.58 Nov. 41 369.95 June 59 539.03 Dec. 30 273.93 Assuming that a simple linear regression model is appropriate, fit the regression model relating stem usage (y) to the average temperature (x). What is the estimate of ? What is the estimate of expected stem usage when the average temperature is 55 F? What change in mean stem usage is expected when the monthly average temperature changes by 1 F? Suppose that the monthly average temperature is 47 F. Calculate the fitted value of y and the corresponding residual. Test for significance of regression using α=0.01 (Use ANOVA). Calculate the r2 of the model. Find a 99% CI for .
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 94E
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- The number of pounds of steam used per month by a chemical plant is thought to be related to the average ambient temperature (in F) for that month. The past year’s usage and temperatures are in the following table:
Month | Temp. | Usage/1000 | Month | Temp. | Usage/1000 |
Jan. | 21 | 185.79 | July. | 68 | 621.55 |
Feb. | 24 | 214.47 | Aug. | 74 | 675.06 |
Mar. | 32 | 288.03 | Sept. | 62 | 562.03 |
Apr. | 47 | 424.84 | Oct. | 50 | 452.93 |
May | 50 | 454.58 | Nov. | 41 | 369.95 |
June | 59 | 539.03 | Dec. | 30 | 273.93 |
- Assuming that a simple linear regression model is appropriate, fit the regression model relating stem usage (y) to the average temperature (x). What is the estimate of ?
- What is the estimate of expected stem usage when the average temperature is 55 F?
- What change in
mean stem usage is expected when the monthly average temperature changes by 1 F? - Suppose that the monthly average temperature is 47 F. Calculate the fitted value of y and the corresponding residual.
- Test for significance of regression using α=0.01 (Use ANOVA).
- Calculate the r2 of the model.
- Find a 99% CI for .
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Part A of question one asks for the variance (sigma squared), not the equation of regression line. Is the variance 2.79 as I listed on my answer sheet?
Maybe my image didn't go through, but I already had the answer to subparts B and C to the question, which you list as #2 and #3.
But I need help with parts D, E, and F.
I have the following answers for D.
d. Y hat (fitted value = 426.46), with residual of -1.62.
e. r squared value = 1.00
g. 99% confidence interval = (-11.63, -1.05)
Thanks
thanks
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