(b) Find the equation of the least squares regression line. (Round your answers to four decimal places.) ý = 78.077 x + .391 Based on this line, what would you predict acrylamide concentration (in micrograms per kg) to be for a frying time of 240 seconds? What is the residual (in micrograms per kg) associated with the observation (240, 190)? (Round your answers to two decimal places.) predicted value micrograms per kg residual micrograms per kg
(b) Find the equation of the least squares regression line. (Round your answers to four decimal places.) ý = 78.077 x + .391 Based on this line, what would you predict acrylamide concentration (in micrograms per kg) to be for a frying time of 240 seconds? What is the residual (in micrograms per kg) associated with the observation (240, 190)? (Round your answers to two decimal places.) predicted value micrograms per kg residual micrograms per kg
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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A STA 1053 HW10 Module10 - STA 1053.003 Spri...
b Acrylamide is a chemical that is sometimes f...
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(b) Find the equation of the least squares regression line. (Round your answers to four decimal places.)
= 78.077 x +
.391
Based on this line, what would you predict acrylamide concentration (in micrograms per kg) to be for a frying time of 240 seconds? What is the residual (in micrograms per
kg) associated with the observation (240, 190)? (Round your answers to two decimal places.)
predicted value
micrograms per kg
residual
micrograms per kg
(c) Look again at the scatterplot from part (a). Which observation is potentially influential? Explain the reason for your choice. (Hint: See Example 4.9.)
The observation (300, 135) is potentially influential because that point has an x value that is far away from the rest of the data set.
The observation (240, 190) is potentially influential because that point has an x value that is far away from the rest of the data set.
The observation (300, 135) is potentially influential because that point has a large residual.
The observation (150, 150) is potentially influential because that point has a large residual.
The observation (150, 150) is potentially influential because that point has an x value that is far away from the rest of the data set.
(d) When the potentially influential observation is deleted from the data set, the equation of the least squares regression line fit to the remaining five observations is
= -44 + 0.83x. Use this equation to predict acrylamide concentration (in micrograms per kg) for a frying time of 240 seconds.
155.2
micrograms per kg
Compare this prediction to the prediction made in part (b).
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b Acrylamide is a chemical that is sometimes f...
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Acrylamide is a chemical that is sometimes found in cooked starchy foods and which is thought to increase the risk of certain kinds of cancer. The paper "A Statistical Regression
Model for the Estimation of Acrylamide Concentrations in French Fries for Excess Lifetime Cancer Risk Assessment"t describes a study to investigate the effect of x = frying time
(in seconds) and y = acrylamide concentration (in micrograms per kg) in french fries. The data in the accompanying table are approximate values read from a graph that
appeared in the paper.
Frying
Time
Acrylamide
Concentration
150
150
240
120
240
190
270
185
300
135
300
275
(a) Construct a scatterplot of these data.
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