For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y=1). The predictor variables are cellularity of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by: π(y=1) In = -2.88 +3.08CELL - 2.5INFIL [1-7(y=1)] 3. What is the probability of observing leukemia remission when the cellularity of the marrow clot section is 0.8 and the proportion of absolute marrow leukemia cell infiltrate is 0.63? OA. -1.991 OB. 0.120 O C. 0.137 O D. 1
For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y=1). The predictor variables are cellularity of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by: π(y=1) In = -2.88 +3.08CELL - 2.5INFIL [1-7(y=1)] 3. What is the probability of observing leukemia remission when the cellularity of the marrow clot section is 0.8 and the proportion of absolute marrow leukemia cell infiltrate is 0.63? OA. -1.991 OB. 0.120 O C. 0.137 O D. 1
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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![For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain
hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y-1). The predictor variables are cellularity
of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by:
π(y=1)
In
= -2.88 +3.08CELL - 2.5INFIL
[1-π(y=1)]
3. What is the probability of observing leukemia remission when the cellularity of the marrow clot section is 0.8 and the proportion of absolute marrow leukemia
cell infiltrate is 0.63?
O A. -1.991
OB. 0.120
OC. 0.137
O D. 1](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3478eb2b-d575-460e-8941-9efa289dcb01%2Fbbc34754-dae1-44e5-a4db-dae412cc2099%2Fsa64w64_processed.jpeg&w=3840&q=75)
Transcribed Image Text:For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain
hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y-1). The predictor variables are cellularity
of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by:
π(y=1)
In
= -2.88 +3.08CELL - 2.5INFIL
[1-π(y=1)]
3. What is the probability of observing leukemia remission when the cellularity of the marrow clot section is 0.8 and the proportion of absolute marrow leukemia
cell infiltrate is 0.63?
O A. -1.991
OB. 0.120
OC. 0.137
O D. 1
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