1. In the model from Exercise 1 with just age as an explanatory variable (a) Compute 95% LR and Wald confidence intervals for the effect of each additional year of age on the log odds that a baby has low birth weight. (b) Interpret the interval, making both a technical statement ("there is 95% confidence...") and a practical one (does the age of the mother seem to affect whether the baby may have low birth weight? 2. For the 2-variable model fit in Exercise 5 of Lecture 7 (a) Use partial LR tests with a = 0.05 to determine which variables seem to contribute significantly to the model for probability of low birth weight. Present test statistics and p-values, and draw conclusions about the results. (b) Perform a single test to see whether both variables can be removed from the model and draw conclusions. Are the results surprising, given the results of part (a)? 5. For the same data, fit the model = logit() Boage + Blwt with glm (). For now, just report the summary results, to see what it looks like with more than one explanatory variable. We will explore this regression more later.