(b) Calculate the equation of the estimated regression line. (Round all numerical values to two decimal places.) y = (c) What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate? (Round your answer to one decimal place.) % (d) Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the line. Delete this observation and recalculate the equation. (Round all numerical values to two decimal places.) y* = Does the new equation appear to differ substantially from the original one (you might consider predicted values)? Yes, there are significant differences.No, there are not significant differences.
(b) Calculate the equation of the estimated regression line. (Round all numerical values to two decimal places.) y = (c) What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate? (Round your answer to one decimal place.) % (d) Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the line. Delete this observation and recalculate the equation. (Round all numerical values to two decimal places.) y* = Does the new equation appear to differ substantially from the original one (you might consider predicted values)? Yes, there are significant differences.No, there are not significant differences.
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
Question
100%
The accompanying data was read from a graph. The independent variable is SO2 deposition rate (mg/m2/d) and the dependent variable is steel weight loss (g/m2).
x | 15 | 18 | 40 | 43 | 45 | 113 |
y | 280 | 350 | 460 | 500 | 560 | 1140 |
(a) Construct a scatter plot .
Does the simple linear regression model appear to be reasonable in this situation?
(b) Calculate the equation of the estimated regression line. (Round all numerical values to two decimal places.)
y =
(c) What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate? (Round your answer to one decimal place.)
%
(d) Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the line. Delete this observation and recalculate the equation. (Round all numerical values to two decimal places.)
y* =
Does the new equation appear to differ substantially from the original one (you might consider predicted values)?
Does the simple linear regression model appear to be reasonable in this situation?
Yes, the scatter plot shows a reasonable linear relationship.No, the scatter plot does not show a reasonable linear relationship.
(b) Calculate the equation of the estimated regression line. (Round all numerical values to two decimal places.)
y =
(c) What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate? (Round your answer to one decimal place.)
%
(d) Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the line. Delete this observation and recalculate the equation. (Round all numerical values to two decimal places.)
y* =
Does the new equation appear to differ substantially from the original one (you might consider predicted values)?
Yes, there are significant differences.No, there are not significant differences.
I just need help with b-d, thanks
 alt="The accompanying data was read from a graph. The independent variable is So, deposition rate (mg/m2/d) and the dependent variable is steel weight loss (g/m2).
15
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y | 280 350 460 500 560 1140
(a) Construct a scatter plot.
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Transcribed Image Text:The accompanying data was read from a graph. The independent variable is So, deposition rate (mg/m2/d) and the dependent variable is steel weight loss (g/m2).
15
18
40
43
45
113
y | 280 350 460 500 560 1140
(a) Construct a scatter plot.
y
y
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800아
800아
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200
200아
X
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
Transcribed Image Text:Does the simple linear regression model appear to be reasonable in this situation?
O Yes, the scatter plot shows a reasonable linear relationship.
O No, the scatter plot does not show a reasonable linear relationship.
(b) Calculate the equation of the estimated regression line. (Round all numerical values to two decimal places.)
y =
(c) What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate? (Round your answer to one decimal place.)
%
(d) Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the line. Delete this observation and recalculate the
equation. (Round all numerical values to two decimal places.)
y* =
Does the new equation appear to differ substantially from the original one (you might consider predicted values)?
O Yes, there are significant differences.
O No, there are not significant differences.
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