For numbers 2-7: Sea lice is a common parasite found among saltwater fish. Presence of the pests are said to be related to pollution in the bodies of water. A total of 50 random sample of fish from a certain bay was obtained. Each fish was analyzed whether an internal parasite (Y-1) was observed or not. Likewise, the amount of estrogenic compounds in the fish blood X₂, ppt) and the sex of the fish (X₂, Male-1 and Female-0), using Female as base category, were recorded. Regression analysis was done and the model is given by In-1.3+0.34X₁ + 1.51.X₂ Macbee wants to validate the model above. He observed 30 random sample of fish from the same bay. He came up with a confusion matrix below. Outcome 0 (with parasite) 1 (without parasite) © A. 40 ⒸB 13.3 O C. 167 O D. 86.7 5. The accuracy of MacBee's model is ___% A Bartlett's test Predicted Probability OB. Levene's test OC Wald's W test <0.5 ● D. t-test 1 2 > 0.5 6. The appropriate test procedure to assess the overall fit of the model is 2 25 7. Suppose in his test for the overall assessment of the model outputs a p-value of 0.0001, the conclusion at a-0.05 is A the predictors are not significant B. there is sufficien: evidence to say that the model with predictors fits OC. there is insufficient evidence to say that the model with predictors fits OD. the model with predictors does not fit significantly
For numbers 2-7: Sea lice is a common parasite found among saltwater fish. Presence of the pests are said to be related to pollution in the bodies of water. A total of 50 random sample of fish from a certain bay was obtained. Each fish was analyzed whether an internal parasite (Y-1) was observed or not. Likewise, the amount of estrogenic compounds in the fish blood X₂, ppt) and the sex of the fish (X₂, Male-1 and Female-0), using Female as base category, were recorded. Regression analysis was done and the model is given by In-1.3+0.34X₁ + 1.51.X₂ Macbee wants to validate the model above. He observed 30 random sample of fish from the same bay. He came up with a confusion matrix below. Outcome 0 (with parasite) 1 (without parasite) © A. 40 ⒸB 13.3 O C. 167 O D. 86.7 5. The accuracy of MacBee's model is ___% A Bartlett's test Predicted Probability OB. Levene's test OC Wald's W test <0.5 ● D. t-test 1 2 > 0.5 6. The appropriate test procedure to assess the overall fit of the model is 2 25 7. Suppose in his test for the overall assessment of the model outputs a p-value of 0.0001, the conclusion at a-0.05 is A the predictors are not significant B. there is sufficien: evidence to say that the model with predictors fits OC. there is insufficient evidence to say that the model with predictors fits OD. the model with predictors does not fit significantly
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 5E
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Transcribed Image Text:For numbers 2-7: Sea lice is a common parasite found among saltwater fish. Presence of the pests are said to be related to pollution in the bodies of water. A total of 50 random sample of fish from a certain bay was obtained. Each fish
was analyzed whether an internal parasite (Y=1) was observed or not. Likewise, the amount of estrogenic compounds in the fish blood (X₁, ppt) and the sex of the fish (X₂, Male=1 and Female=0), using Female as base category, were
recorded. Regression analysis was done and the model is given by:
= -1.3 +0.34X₁ + 1.51X₂
(y=1)
1-(y=1)
Macbee wants to validate the model above. He observed 30 random sample of fish from the same bay. He came up with a confusion matrix below.
Outcome
0 (with parasite)
1 (without parasite)
A. 4.0
B. 13.3
ⒸC. 16.7
5. The accuracy of MacBee's model is
D. 86.7
A. Bartlett's test
B. Levene's test
Predicted Probability
C. Wald's W test
< 0.5
D. t-test
1
2
6. The appropriate test procedure to assess the overall fit of the model is _______
> 0.5
2
25
7. Suppose in his test for the overall assessment of the model outputs a p-value of 0.0001, the conclusion at a = 0.05 is
A. the predictors are not significant
B. there is sufficien: evidence to say that the model with predictors fits
ⒸC. there is insufficient evidence to say that the model with predictors fits
ⒸD. the model with predictors does not fit significantly
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