For Table 4.3, let Y = 1 if a crab has at least one satellite, and Y = 0 otherwise. Using x = weight, fit the linear probability model. a. Use ordinary least squares. Interpret the parameter estimates. Find the estimated probability at the highest observed weight (5.20 kg). Comment. b. Fit the logistic regression model. Show that the fitted

Chapter 4, Problems #5

This problem has been solved!


Do you need an answer to a question different from the above? Ask your question!
For Table 4.3, let Y = 1 if a crab has at least one satellite, and Y = 0 otherwise. Using x = weight, fit the linear probability model.

a. Use ordinary least squares. Interpret the parameter estimates. Find the estimated probability at the highest observed weight (5.20 kg). Comment.

b. Fit the logistic regression model. Show that the fitted probability at a weight of 5.20 kg equals 0.9968.

c. Fit the probit model. Find the fitted probability at 5.20 kg.


Table 4.3:

Number of Crab Satellites by Female's Characteristics

Related Book For answer-question

Categorical Data Analysis

2nd edition

Authors: Alan Agresti

ISBN: 978-0471360933