Give R commands and examples of the following: a. How to find the least square estimates and maximum likelihood estimators? (Hint: the least squares estimates are the same as the MLEs of the GLM assuming normal rather than binomial random component) b. Use ordinary least squares. Find the predicted probability at the highest observed weight c.fit model using maximum likelihood estimation, treating Y as a binary variable in R d. How to fit logistic regression model in R (and how to derive the estimated logit at a weight of 5.2 kg and derive corresponding estimated probability pi hat. e. HOw to fit a poison regression model wit the log link. report the prediction equation f. Allow overdispersion by fitting negative binomial loglinear model.

1. Give R commands and examples of the following: a. How to find the least square estimates and
maximum likelihood estimators? (Hint: the least squares estimates are the same as the MLEs of
the GLM assuming normal rather than binomial random component) b. Use ordinary least
squares. Find the predicted probability at the highest observed weight c.fit model using maximum
likelihood estimation, treating Y as a binary variable in R d. How to fit logistic regression model in
R (and how to derive the estimated logit at a weight of 5.2 kg and derive corresponding estimated
probability pi hat. e. HOw to fit a poison regression model wit the log link. report the prediction
equation f. Allow overdispersion by fitting negative binomial loglinear model