An article in the Journal of the Environmental Engineering Division ("Least Squares Estimates of BOD Parameters," Vol. 106, 1980, pp. 1197-1202) describes the results of testing a sample from the Holston River below Kingport, TN, during August 1977. The biochemical oxygen demand (BOD) test is conducted over a period of time in days. The resulting data is shown below: Time (days) BOD (mg/liter)| 1 0.6 0.7 1.5 6. 1.9 8 2.1 10 2.6 12 2.9 14 3.7 16 3.5 18 3.7 20 3.8 Minitab output resulting from fitting a simple linear regression model with time as the explanatory variable and BOD as the response follows. Predictor Coef SE Coef Constant 0.6578 0.1657 3.97 0.003 Time 0.17806 0.01400 12.72 0.000 S-0.287281 R-Sq = 94.7% R-Sq(adj) = 94.1% Analysis of Variance Source DF SS MS F Regression 13.344 13.344 161.69 0.000 Residual 0.743 0.083 Error Total 10 14.087 (a) Assuming that a simple linear regression model is appropriate, estimate the regression model relating BOD (y) to the time (x). Round your final answers to 4 decimal places. = What is the estimate of a? Round your final answer to 3 decimal places. a = i
An article in the Journal of the Environmental Engineering Division ("Least Squares Estimates of BOD Parameters," Vol. 106, 1980, pp. 1197-1202) describes the results of testing a sample from the Holston River below Kingport, TN, during August 1977. The biochemical oxygen demand (BOD) test is conducted over a period of time in days. The resulting data is shown below: Time (days) BOD (mg/liter)| 1 0.6 0.7 1.5 6. 1.9 8 2.1 10 2.6 12 2.9 14 3.7 16 3.5 18 3.7 20 3.8 Minitab output resulting from fitting a simple linear regression model with time as the explanatory variable and BOD as the response follows. Predictor Coef SE Coef Constant 0.6578 0.1657 3.97 0.003 Time 0.17806 0.01400 12.72 0.000 S-0.287281 R-Sq = 94.7% R-Sq(adj) = 94.1% Analysis of Variance Source DF SS MS F Regression 13.344 13.344 161.69 0.000 Residual 0.743 0.083 Error Total 10 14.087 (a) Assuming that a simple linear regression model is appropriate, estimate the regression model relating BOD (y) to the time (x). Round your final answers to 4 decimal places. = What is the estimate of a? Round your final answer to 3 decimal places. a = i
MATLAB: An Introduction with Applications
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Related questions
Question
![An article in the Journal of the Environmental Engineering Division ("Least Squares Estimates of BOD Parameters," Vol. 106, 1980, pp.
1197-1202) describes the results of testing a sample from the Holston River below Kingport, TN, during August 1977. The
biochemical oxygen demand (BOD) test is conducted over a period of time in days. The resulting data is shown below:
Time (days) BOD (mg/liter)
1
0.6
2
0.7
4
1.5
1.9
8
2.1
10
2.6
12
2.9
14
3.7
16
3.5
18
3.7
20
3.8
Minitab output resulting from fitting a simple linear regression model with time as the explanatory variable and BOD as the response
follows.
Predictor
Coef
SE Coef
T
P
Constant
0.6578
0.1657
3.97
0.003
Time
0.17806
0.01400
12.72
0.000
S= 0.287281 R-Sq = 94.7% R-Sq(adj) = 94.1%
Analysis of Variance
Source
DF
S
MS
F
P
Regression
1
13.344
13.344
161.69
0.000
Residual
9
0.743
0.083
Error
Total
10
14.087
(a) Assuming that a simple linear regression model is appropriate, estimate the regression model relating BOD (y) to the time (x).
Round your final answers to 4 decimal places.
What is the estimate of a?
Round your final answer to 3 decimal places.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9a0def38-59dd-482e-955f-2a69fd23f78a%2F14a074d5-4f4e-4947-aa2c-3b1581d1a2f0%2Fbnf7tzs_processed.png&w=3840&q=75)
Transcribed Image Text:An article in the Journal of the Environmental Engineering Division ("Least Squares Estimates of BOD Parameters," Vol. 106, 1980, pp.
1197-1202) describes the results of testing a sample from the Holston River below Kingport, TN, during August 1977. The
biochemical oxygen demand (BOD) test is conducted over a period of time in days. The resulting data is shown below:
Time (days) BOD (mg/liter)
1
0.6
2
0.7
4
1.5
1.9
8
2.1
10
2.6
12
2.9
14
3.7
16
3.5
18
3.7
20
3.8
Minitab output resulting from fitting a simple linear regression model with time as the explanatory variable and BOD as the response
follows.
Predictor
Coef
SE Coef
T
P
Constant
0.6578
0.1657
3.97
0.003
Time
0.17806
0.01400
12.72
0.000
S= 0.287281 R-Sq = 94.7% R-Sq(adj) = 94.1%
Analysis of Variance
Source
DF
S
MS
F
P
Regression
1
13.344
13.344
161.69
0.000
Residual
9
0.743
0.083
Error
Total
10
14.087
(a) Assuming that a simple linear regression model is appropriate, estimate the regression model relating BOD (y) to the time (x).
Round your final answers to 4 decimal places.
What is the estimate of a?
Round your final answer to 3 decimal places.
![Round your final answer to 3 decimal places.
(b) What is the estimate of expected BOD level when the time is 13 days?
Round your final answer to 3 decimal places.
(c) What change in mean BOD is expected when the time increases by 2 days?
Round your final answer to 4 decimal places.
(d) Suppose the time used is 2 days. Calculate the fitted value of y and the corresponding residual.
Round your final answers to 4 decimal places.
ŷ = i
(e) The following is a graph of ŷ versus the corresponding observed values y;-
Scatterplot of fitted vs BOD
45-
4.0
3.5-
30
25
20
15
10
0.5
10
1.5
20
30
35
BOD
Which of the following describes what this plot would look like if the relationship between y and x was a deterministic (no random
error) straight line?
the points would be in a completely random pattern
the points would all be equal
O the points would fall on a horizontal line
O the points would fall along a 45° line
(f) Does the plot actually obtained indicate that time is an effective regressor variable in predicting BOD?
pauy
O O](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9a0def38-59dd-482e-955f-2a69fd23f78a%2F14a074d5-4f4e-4947-aa2c-3b1581d1a2f0%2Fltmv2nv_processed.png&w=3840&q=75)
Transcribed Image Text:Round your final answer to 3 decimal places.
(b) What is the estimate of expected BOD level when the time is 13 days?
Round your final answer to 3 decimal places.
(c) What change in mean BOD is expected when the time increases by 2 days?
Round your final answer to 4 decimal places.
(d) Suppose the time used is 2 days. Calculate the fitted value of y and the corresponding residual.
Round your final answers to 4 decimal places.
ŷ = i
(e) The following is a graph of ŷ versus the corresponding observed values y;-
Scatterplot of fitted vs BOD
45-
4.0
3.5-
30
25
20
15
10
0.5
10
1.5
20
30
35
BOD
Which of the following describes what this plot would look like if the relationship between y and x was a deterministic (no random
error) straight line?
the points would be in a completely random pattern
the points would all be equal
O the points would fall on a horizontal line
O the points would fall along a 45° line
(f) Does the plot actually obtained indicate that time is an effective regressor variable in predicting BOD?
pauy
O O
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