c) Suppose that you have estimated P(Y) = G[0.4 – 1.2X] using a Logit model, where G is a cumulative logistic function, G(z)=exp(z)/[1+exp(z)], and that the sample mean of X is 0.56. The predicted likelihood of Y happening when X is 0.5 is .450166. %3D
c) Suppose that you have estimated P(Y) = G[0.4 – 1.2X] using a Logit model, where G is a cumulative logistic function, G(z)=exp(z)/[1+exp(z)], and that the sample mean of X is 0.56. The predicted likelihood of Y happening when X is 0.5 is .450166. %3D
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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![True or false, and why?
c) Suppose that you have estimated P(Y) = G[0.4 – 1.2X] using a Logit model, where G is a
cumulative logistic function, G(z)=exp(z)/[1+exp(z)], and that the sample mean of X is 0.56.
The predicted likelihood of Y happening when X is 0.5 is .450166.
%3D](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa19acced-d982-4027-ac07-c40d3f5d7e7e%2Fc80dbb7a-51d2-4a92-b442-509c8d2614b4%2Fxk8zrb_processed.jpeg&w=3840&q=75)
Transcribed Image Text:True or false, and why?
c) Suppose that you have estimated P(Y) = G[0.4 – 1.2X] using a Logit model, where G is a
cumulative logistic function, G(z)=exp(z)/[1+exp(z)], and that the sample mean of X is 0.56.
The predicted likelihood of Y happening when X is 0.5 is .450166.
%3D
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