The exam will cover material from chapters 8 and 9. You should be familiar with all definitions presented in the text or in class notes.
Given a point estimate, you should be able to determine its bias and mean square error, and bounds on the error of estimation.
You should be able to use the pivotal method to construct confidence intervals.
You should be able to apply the large-sample methods of section 8.6 and small-sample confidence interval methods of section 8.8.
You should be able to compute the sample size required for a given size confidence interval using the material in section 8.7, and apply the methods of section 8.9 for confidence intervals for the variance.
You should be able to determine the relative efficiency of two unbiased estimators, and determine whether an unbiased estimator is consistent. You should be able to apply theorems 9.1, 9.2, and 9.3.
You should be familiar with the definition of a sufficient statistic, be able to apply the definition directly, and be able to use the factorization theorem to find sufficient statistics.
You should be familiar with the Rao-Blackwell theorem and how to use it to find MVUE's.
You should be able to find estimators using the method of moments and maximum likelihood method.
You should be able to apply the formula from section 9.8 for large-sample properties of maximum likelihood estimators (the formula will be supplied).
The material from the back cover of the text and any required critical values will be supplied.