ifteen (15) samples of water were collected from a certain treatment facility in order to gain some insight regarding the amount of coliform in the urban pipeline. The concentration of the coliform easured in parts per million (ppm), per liter. Suppose that the mean at the treatment facility is not as important as the upper extreme of the distribution of the amount of coliform detected. The oncern is whether the concentration of coliform is too large. Readings for the 15 water samples gave a sample mean of 3.84 ppm per liter and a standard deviation of 3.07 ppm per liter. Assume at the readings are a random sample from a normal distribution. alculate a Prediction Interval (upper 95% prediction limit) and a Tolerance Limit (95% upper tolerance limit that exceeds 95% of the population values). Interpret both; that is, tell what each ommunicates about the upper extreme of the distribution of coliform at the sampling in the treatment facility. Oa. Prediction Upper Limit: Xn+1 s9.398. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.86. Hence, we are 95% confident that a limit of 11.86 will contain 95%% of the coliform measurement in the water samples Ob. Prediction Upper Limit: Xn+1 s9.424. This means that a new obsernvation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.72. Hence, we are 95% confident that a limit of 11.72 will contain 95% of the coliform measurement in the water samples Oc. Prediction Upper Limit: Xn+1 s 10.597. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.72. Hence, we are 95% confident that a limit of 11.72 will contain 95% of the coliform measurement in the water samples Od. Prediction Upper Limit: Xn+1 s 10.641. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 12.91. Hence, we are 95% confident that a limit of
ifteen (15) samples of water were collected from a certain treatment facility in order to gain some insight regarding the amount of coliform in the urban pipeline. The concentration of the coliform easured in parts per million (ppm), per liter. Suppose that the mean at the treatment facility is not as important as the upper extreme of the distribution of the amount of coliform detected. The oncern is whether the concentration of coliform is too large. Readings for the 15 water samples gave a sample mean of 3.84 ppm per liter and a standard deviation of 3.07 ppm per liter. Assume at the readings are a random sample from a normal distribution. alculate a Prediction Interval (upper 95% prediction limit) and a Tolerance Limit (95% upper tolerance limit that exceeds 95% of the population values). Interpret both; that is, tell what each ommunicates about the upper extreme of the distribution of coliform at the sampling in the treatment facility. Oa. Prediction Upper Limit: Xn+1 s9.398. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.86. Hence, we are 95% confident that a limit of 11.86 will contain 95%% of the coliform measurement in the water samples Ob. Prediction Upper Limit: Xn+1 s9.424. This means that a new obsernvation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.72. Hence, we are 95% confident that a limit of 11.72 will contain 95% of the coliform measurement in the water samples Oc. Prediction Upper Limit: Xn+1 s 10.597. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.72. Hence, we are 95% confident that a limit of 11.72 will contain 95% of the coliform measurement in the water samples Od. Prediction Upper Limit: Xn+1 s 10.641. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 12.91. Hence, we are 95% confident that a limit of
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Transcribed Image Text:Fifteen (15) samples of water were collected from a certain treatment facility in order to gain some insight regarding the amount of coliform in the urban pipeline. The concentration of the coliform is
measured in parts per million (ppm), per liter. Suppose that the mean at the treatment facility is not as important as the upper extreme of the distribution of the amount
concern is whether the concentration of coliform is too large. Readings for the 15 water samples gave a sample mean of 3.84 ppm per liter and a standard deviation of 3.07 ppm per liter. Assume
that the readings are a random sample from a normal distribution.
i coliform detected. The
Calculate a Prediction Interval (upper 95% prediction limit) and a Tolerance Limit (95% upper tolerance limit that exceeds 95% of the population values). Interpret both; that is, tell what each
communicates about the upper extreme of the distribution of coliform at the sampling in the treatment facility.
O a. Prediction Upper Limit: Xn+1s9.398. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.86. Hence, we are 95% confident that a limit of
11.86 will contain 95% of the coliform measurement in the water samples
O b. Prediction Upper Limit: Xn+1s9.424. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.72. Hence, we are 95% confident that a limit of
11.72 will contain 95% of the coliform measurement in the water samples
O. Prediction Upper Limit: Xn+1 s 10.597. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 11.72. Hence, we are 95% confident that a limit of
11.72 will contain 95% of the coliform measurement in the water samples
O d. Prediction Upper Limit: Xn+1 s 10.641. This means that a new observation will have a chance of 95% to fall below the upper limit. Tolerance Upper Limit: 12.91. Hence, we are 95% confident that a limit of
12.91 will contain 95% of the coliform measurement in the water samples
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