Japan's high population density has resulted in a multitude of resource-usage problems. One especially serious difficulty concerns waste removal. The article "Innovative Sludge Handling Through Pelletization Thickening"+ reported the development of a new compression machine for processing sewage sludge. An important part of the investigation involved relating the moisture content of compressed pellets (y, in %) to the machine's filtration rate (x, in kg-DS/m/hr). Consider the following data. X 125.5 98.3 201.3 147.3 146.0 124.7 112.4 120.0 161.1 178.9 y 78.0 76.6 81.5 79.7 78.3 78.4 77.5 77.2 80.2 80.1 x 159.5 145.6 75.3 151.4 144.3 124.8 199.0 132.4 159.5 110.8 y 80.1 79.0 76.8 78.4 79.4 78.0 81.3 = 77.1 79.0 78.6 Relevant summary quantities are x, = 2818.1, 1575.2, x² = 415,967.23, xy, = 222,717.02, y = 124,100.72. Also, x = 140.905, y= 78.76, Sxx = 18,882.8495, Sxy= 763.464, and SSE = 7.429. The estimated standard deviation is o = 0.642 and the equation of the least squares line is y=73.124 + 0.040x. Consider the filtration rate-moisture content data introduced above (a) Compute a 90% CI for Ao + 125₁, true average moisture content when the filtration rate is 125. (Round your answers to three decimal places.) (b) Predict the value of moisture content for a single experimental run in which the filtration rate is 125 using a 90% prediction level. (Round your answers to three decimal places.) How does this interval compare to the interval of part (a)? Why is this the case? The width of the confidence interval in part (a) is --Select-- the width of the prediction interval in part (b) since the --Select--- interval must account for both interval must account for both the uncertainty in knowing the value of the population mean in addition to the data scatter. the uncertainty
Japan's high population density has resulted in a multitude of resource-usage problems. One especially serious difficulty concerns waste removal. The article "Innovative Sludge Handling Through Pelletization Thickening"+ reported the development of a new compression machine for processing sewage sludge. An important part of the investigation involved relating the moisture content of compressed pellets (y, in %) to the machine's filtration rate (x, in kg-DS/m/hr). Consider the following data. X 125.5 98.3 201.3 147.3 146.0 124.7 112.4 120.0 161.1 178.9 y 78.0 76.6 81.5 79.7 78.3 78.4 77.5 77.2 80.2 80.1 x 159.5 145.6 75.3 151.4 144.3 124.8 199.0 132.4 159.5 110.8 y 80.1 79.0 76.8 78.4 79.4 78.0 81.3 = 77.1 79.0 78.6 Relevant summary quantities are x, = 2818.1, 1575.2, x² = 415,967.23, xy, = 222,717.02, y = 124,100.72. Also, x = 140.905, y= 78.76, Sxx = 18,882.8495, Sxy= 763.464, and SSE = 7.429. The estimated standard deviation is o = 0.642 and the equation of the least squares line is y=73.124 + 0.040x. Consider the filtration rate-moisture content data introduced above (a) Compute a 90% CI for Ao + 125₁, true average moisture content when the filtration rate is 125. (Round your answers to three decimal places.) (b) Predict the value of moisture content for a single experimental run in which the filtration rate is 125 using a 90% prediction level. (Round your answers to three decimal places.) How does this interval compare to the interval of part (a)? Why is this the case? The width of the confidence interval in part (a) is --Select-- the width of the prediction interval in part (b) since the --Select--- interval must account for both interval must account for both the uncertainty in knowing the value of the population mean in addition to the data scatter. the uncertainty
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
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100%
options from the "select" windows:
first: smaller/equal to/less than
second: prediction/confidence
Transcribed Image Text:Japan's high population density has resulted in a multitude of resource-usage problems. One especially serious difficulty concerns waste removal. The article "Innovative Sludge Handling Through Pelletization Thickening"+ reported the development of a new compression
machine for processing sewage sludge. An important part of the investigation involved relating the moisture content of compressed pellets (y, in %) to the machine's filtration rate (x, in kg-DS/m/hr). Consider the following data.
X 125.5 98.3 201.3 147.3 146.0 124.7 112.4 120.0 161.1 178.9
y 78.0 76.6 81.5 79.7 78.3 78.4 77.5 77.2 80.2 80.1
x 159.5 145.6 75.3 151.4 144.3 124.8 199.0 132.4 159.5 110.8
y 80.1 79.0 76.8 78.4 79.4 78.0 81.3
77.1 79.0 78.6
=
Relevant summary quantities are x, = 2818.1, 1575.2, x² = 415,967.23, xy, 222,717.02, y = 124,100.72. Also, x = 140.905, y = 78.76, Sxx = 18,882.8495, Sxy=763.464, and SSE = 7.429. The estimated standard deviation is o = 0.642
=
and the equation of the least squares line is y= 73.124 + 0.040x.
Consider the filtration rate-moisture content data introduced above
(a) Compute a 90% CI for + 125₁, true average moisture content when the filtration rate is 125. (Round your answers to three decimal places.)
(b) Predict the value of moisture content for a single experimental run in which the filtration rate is 125 using a 90% prediction level. (Round your answers to three decimal places.)
How does this interval compare to the interval of part (a)? Why is this the case?
The width of the confidence interval in part (a) is-Select-- the width of the prediction interval in part (b) since the ---Select--- interval must account for both
interval must account for both the uncertainty in knowing the value of the population mean in addition to the data scatter.
the uncertainty
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