Statistics for Engineers and Scientists
4th Edition
ISBN: 9780073401331
Author: William Navidi Prof.
Publisher: McGraw-Hill Education
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Textbook Question
Chapter 7.4, Problem 1E
The following output (from MINITAB) is for the least-squares fit of the model ln y = β0 + β1 ln x + ε, where y represents the monthly production of a gas well and x represents the volume of fracture fluid pumped in. (A
- a. What is the equation of the least-squares line for predicting ln y from ln x?
- b. Predict the production of a well into which 2500 gal/ft of fluid have been pumped.
- c. Predict the production of a well into which 1600 gal/ft of fluid have been pumped.
- d. Find a 95% prediction interval for the production of a well into which 1600 gal/ft of fluid have been pumped. (Note: In 1600 = 7.3778.)
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Question 1
Provide an algebraic proof that the least squares estimator is not consistent when Cov(x,e)=0 with the regression model y =B1+B2E(x)+e where E(e)=0So that E(y) = B1 + B2E(x)
The following Minitab display gives information regarding the relationship between the body weight of a child (in kilograms) and the metabolic rate of the child (in 100 kcal/ 24 hr).
Predictor Coef SE Coef T PConstant 0.8570 0.4148 2.06 0.84Weight 0.38243 0.02978 13.52 0.000
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y^= ______ + _____x
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Table 14.17
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Bo = 10.3676 (.3710)
B1 = .0500 (<.001)
B2 = 6.3218 (.0152)
B3 = -11.1032 (.0635)
B4 = -.4319 (.0002)
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Chapter 7 Solutions
Statistics for Engineers and Scientists
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