Stat 534 - Spring 2007 - Homework Guidelines and Suggestions

Statistics is best learnt by doing. The homework problems are intended to help you understand the methods we discuss in class, and apply them to solve problems. I also try to set homework problems that make interesting points.

There will be three homework sets, one for each of the three major sections of the course. They will be distributed near the end of the appropriate set of lectures and due approximately two weeks later. Each homework set will consist of five problems. Some problems may have multiple parts. You are to turn in answers to four of the five problems. The first few problems are intended to be simpler than the last few. However, the choice of which to ignore is yours. In general, the problems will be:

  • An ecological question and a set of data. You are to analyze the data set and answer the question.
  • Some theoretical question(s) about the methods.
  • A more complicated ecological question and data set.
  • More complicated theoretical question(s) about the methods.
  • Something interesting, probably a data question, but perhaps not.

    You are encouraged to work together on the problems. I encourage groups to include ecologists and statisticians. This year's class is relatively small; the entire class can be a single group. However, you must each write your own answers. Copying will not be tolerated.

    Answers to data questions should be in the following form:

  • 'Executive summary' or abstract: short statement of question, approach, and answer. Should be no more than one paragraph. No formulae or technical language here. This should be written for the busy biologist or wildlife manager.
  • Approach: Describe your model or approach. Briefly explain why you chose it. Describe computational approach. If you considered multiple models, do not explain all of them in detail. Just say what you considered and why you rejected it.
  • Answer: answer the ecological question(s) using the 'final' model. Make sure you provide the context for the answer. For example, saying 'Estimated Phi equals 0.2349887' is not a sufficient answer because it does not provide context. You must interpret the answer. Estimates of precision (or confidence intervals) are (almost) always useful.
  • Critique: use model diagnostics (if appropriate and available) or other information to critique your answer. What, if any, are the weaknesses or problematic assumptions? Another way to critique your answer is to discuss what are better models/methods to use if you had more time. You should discuss (briefly) why each model or method would be more appropriate. I do not want a laundry list of all possible analyses.

    I expect total length to be no more than three pages for each data problem. It may be considerably less.

    Please ask me if you have any questions about the problems. I am very willing to give advice, especially with computing.

    I give you two weeks to work on the assignment because I don't think the problems can be answered overnight. Please do not wait until the last day to start working on them.