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COURSE INFORMATION

Instructor:

• Sandra McBride, Visiting Assistant Professor, Department of Statistical Science, 221 Old Chemistry Building, sandra at stat.duke.edu, 684-4608

Teaching Assistants:

• Michael Wolosin, michael.wolosin at duke.edu, Ph.D. student, Ecology.

• Dan Olstein, dho at duke.edu, MEM student, Nicholas School of the Environment and Earth Sciences

Course Overview:

This course will focus on exploratory analysis of data, graphical methods, building and fitting models, investigating assumptions of models, and interpreting the results of statistical models. A major focus of our work will be to learn to write literate data analysis reports, and to develop skills to critique statistical analyses. Many of the examples in the class will come from the environmental sciences.

The topics will include:

• Univariate and multivariate linear regression: model construction, critique, and correction using graphical residual analysis

• Comparisons of proportions or odds; models for tables of counts

• Logistic regression for binary response variables and binary count data

• Bayesian approaches to model selection

• Log-linear regression for Poisson counts

• Use of a standard statistical software package for applied data analysis: applications and examples emphasizing the biological and environmental sciences

Prerequisites for Sta 240 / ENV 298.01

• A previous statistics course, at the level of STA101, STA102 or STA210, is required for this course. It is the responsibility of the student to identify areas in which his/her background might be weak, and to review as necessary. Suggested readings and review topics will be provided.

• The main reference text for this class is:

  D. Moore, G. McCabe. Introduction to the Practice of Statistics. W.H. Freeman & Co., 1998. Students whose backgrounds in basic statistics are weak should plan to purchase this book and use it to supplement the course textbook.

  It is assumed that you are familiar with the following material in this book:

  • descriptive statistics: Sections 1.1, 1.2, 2.1

  • probability distributions and random variables: Sections 1.3, 4.1, 4.2, 4.3, 4.5

  • sampling and basic experimental design principles: Chapter 3

  • hypothesis testing and confidence intervals: Chapter 6

  • correlation: Section 2.2

  • the distribution of a sample mean and the Central Limit Theorem: Section 4.4, 5.2

  • one-way analysis of variance: Chapter 12

  • simple linear regression: Section 2.3, 2.4

• The concepts above are covered in the 100-level statistics courses offered in Duke Statistics.

• The School of the Environment gives a statistics diagnostic test to its incoming masters students. It is assumed that you demonstrated proficiency in the topics above on this test. It is to your benefit to take this on-line diagnostic test, since it also provides guidelines for review.

Class Meeting Times: Tuesdays and Thursdays: 12:40 - 1:55. LSRC A247

Computer Lab Sections: As part of the course, students are expected to attend one of the weekly lab sessions, which will emphasize homework questions and computing issues. There will be 2 sections of lab to be held Wednesdays in 153 LSRC.

• 9:10-10:00 am

• 10:30-11:20 am

Required Text: