• Lecture: Tu 3:40 - 5:00, Th 3:40-5:00 MBB 1428
• Instructor: Dr. Philip Dixon, pdixon@iastate.edu, 120 Snedecor, 4-2142
• Office Hours: Thursday 2-3, Friday 1-2.
  
• Review / Help: during office hours
  
• Questions?: Please feel free to e-mail me anytime (pdixon@iastate.edu) with questions or comments.
• Class Web site: http://www.public.iastate.edu/~pdixon/stat534
  Copies of the syllabus, homework assignments, data sets and example programs will be available here.
• Text: None
  
• Reading materials: Various assigned readings will be available in the Statistics Reading room, 115 Snedecor. See Norma to borrow the material to make a copy.
• Goals:
  • Learn methods used to answer ecological questions.
  • Understand the statistical theory for those methods.
  • Illustrate classical and modern statistical inference using some non-standard problems.
  • Be able to apply statistical methods and theory to novel problems.
• Grading:
  3 Homework sets: 100 points each.
  Project: 100 points.
  No tests.

  Homeworks are due at 5pm on the assigned date. Late homework will be penalized 5 points per day late.

• Computing:
  This course emphasizes data analysis to answer questions. This will require using statistical computing packages. Unfortunately, no one package does everything well. You may use whatever tools are appropriate to do the necessary computations. I expect that most of you will use SAS or R; I can help with those packages. In particular, I will distribute examples of SAS and R code on the class web site. Some of you may be familiar with specialized programs developed for certain parts of the course (e.g. MARK for estimation of population parameters). You are free to use that program, but I will not lecture about it.

Weeks  Dates         Topic

 1- 5   Aug 21-Sep 20 Estimation of population parameters
		       (population size, survival, detectability)
		       Mark recapture and related methods
                       
 6-10   Sep 25-Oct 25  Population modeling
		       Matrix models
		       Stochastic matrix models
		       Combining models and data
                       Models with density dependence
                       Bayesian hierarchical modeling
		       Life tables as a response (if time available)

11-13  Oct 30-Nov 15 Spatial point pattern analysis
		       Nearest neighbor analysis
		       Ripley's K and pair correlation functions 
                       Multi-type analysis (spatial segregation)
		       Models for point patterns
                       Fitting models
		       Point patterns as responses

14-15 Nov 27-Dec Dec 6  Catch up / To be determined by class interest

Possible topics for the last two weeks: 

 Your suggestions, especially methods or problems specific to your research
 Further extensions of topics already discussed.
 Behavioural statistics, especially analysis of event sequences.
 Resource selection / habitat preference analysis
 Home range estimation and related issues

Readings: Assigned readings will provide background, additional details, or another presentation of the lecture material. Citations will be distributed in lecture. Norma in the Statistics Reading Room, 115 Snedecor, will have a master copy that you can borrow. It will help if you read the assigned material soon after the appropriate lectures.

Homework: Statistics is best learnt by doing. The homework problems are chosen to give you practice in using the methods, interpreting the results, and understanding the theory. The intent is to understand and be able to apply lecture concepts, so discussion with friends and classmates is encouraged. However, you must write up your own solutions. Copying papers is not a good way to learn and will not be tolerated.

More details on the homework policy and guidelines are on the Homework Guidelines page.

Disability accommodation: Iowa State University complies with the Americans with Disabilities Act and Sect 504 of the Rehabilitation Act. If you have a disability and anticipate needing accommodation(s) in this course, please contact Philip Dixon within the first two weeks of the semester. Retroactive requests for accommodations will not be honored. Before meeting with me, you need to obtain a SAAR form with recommendations for accommodations from the Disability Resources Office, Room 1076, Student Services Building. Their telephone number is 515-294-6624.

Academic Honesty Policy: The ISU academic honesty policy is printed in the University catalog and available online. To clarify how this applies to your work in this class:
On homework assignments: I encourage you to help each other interpret the homework problems, write code, debug code, and interpret the output. You may share code, but I encourage you to understand that code even if you didn't write it. I do require you to write your answers in your own words.
On the project: I encourage pairs to work together and write a single report. I will ask each person to assess the relative contribution of each person. The grade will be assigned proportionately.