For the horseshoe crab data , ?t the logistic regr...
For the horseshoe crab data , fit the logistic regression model for π =probability of a satellite, using weight as the predictor. a. Report the ML prediction equation. b. Findat the weight values 1.20, 2.44, and 5.20kg, which are the sample minimum, mean, and maximum. c. Find the weight at which. d. At the weight value found in (c), give a linear approximation for the estimated effect of (i) a 1kg increase in weight. This represents a relatively large increase, so convert this to the effect of (ii) a 0.10kg increase, and (iii) a standard deviation increase in weight (0.58kg). e. Construct a 95% confidence interval to describe the effect of weight on the odds of a satellite. Interpret. f. Conduct theWald or likelihood-ratio test of the hypothesis that weight has no effect. Report the P-value, and interpret. Note: you can get the data in the R package "icda" which is named by "horseshoecrabs".