Key Links

• Course Calendar Readings, handouts, homework.

• Blackboard site Includes announcements, class discussion group, homework solutions, and grades.

• Practice Problems

• Office Hours & Locations

• Splus Guide updated periodically

Course Information

Instructor, TAs	Course Overview	Prerequisites	Meeting Times, Labs
Textbooks	Software	Course policies	Grading scheme

Instructor:

Sandra McBride, Visiting Assistant Professor, Department of Statistical Science (Duke Statistics), 221 Old Chemistry Building. Nicholas School of the Environment and Earth Sciences (NSEES) office: LSRC A125. Duke Voicemail: (919) 613-8029. Duke Statistics Office: (919) 684-8025. email: sandra "at" stat.duke.edu

• Abel Rodriguez, Ph.D. student, Department of Statistical Science,
  ar52 "at" stat.duke.edu
• Betsy Albright, Ph.D. student, Nicholas School of the Environment and Earth Sciences,
  elizabeth.albright "at" duke.edu
• Lauren Hauser, Masters of Environmental Management student, Nicholas School of the Environment and Earth Sciences,
  lh22 "at" duke.edu
• Shinsuke Murakami, Masters of Environmental Management student, Nicholas School of the Environment and Earth Sciences,
  shinsuke.murakami "at" duke.edu

Course Overview:

This course is an introduction to modeling, estimation, and hypothesis testing for applied problems in the environmental sciences. Emphasis is on comparisons of means between two or more groups, using both parametric and non-parametric methods. A major focus of our work will be to learn to write literate data analysis reports, and to develop skills to critique statistical analyses. Examples will come from the environmental sciences.

Topics:

• Graphical and exploratory data analysis
• Inference using t-distributions
• Power
• One-way analysis of variance
• Linear combinations and multiple comparisons of means
• Introduction to simple linear regression and multiple regression
• Relationship between 2-way ANOVA and regression.
• Non-parametric methods, permutation tests, bootstrap methods
• Use of a statistical computing software package (S-plus)

Prerequisites for STA 240 / ENV 210

The main reference text for this class is:

D. Moore, G. McCabe. Introduction to the Practice of Statistics. W.H. Freeman & Co., 4th edition Students whose backgrounds in basic statistics are weak should plan to purchase this book and use it to supplement the course textbook.

As prerequisite material, 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 100-level statistics courses offered in Duke Statistics, as well as STA210A.

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.

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 3 sections of lab to be held Mondays in 153 LSRC: 8:00-8:50 am, 9:10-10:00 am, 10:30-11:20 am.

Texts and Software:

• Fred L. Ramsey and Daniel W. Schafer, The Statistical Sleuth: A Course in Methods of Data Analysis, 2nd Edition, 2002.
  • Student Solutions Guide.

• Datasets from the Statistical Sleuth. Case studies at the beginning of each chapter are denoted "Case0102.ASC" (Chapter 1 Case Study 2) and "Ex0102" for exercises.

Suggested background text for prerequisite topics:

• D. Moore, G. McCabe. Introduction to the Practice of Statistics, 4th edition. W.H. Freeman & Co. (This link also gives supplementary questions and answers)

• A course at this level is a prerequisite for this course.

Course Policies

The Nicholas School of the Environment and Earth Sciences (NSEES) advocates the highest standards of professional ethics and academic integrity. Students and faculty have developed an honor code for the school which is distributed to all students prior to matriculation and discussed during orientation. Students are expected to follow the NSEES Honor Code.

All written assignments must be done independently. This includes computations, Splus output, graphs, answers to questions and discussion of results.Copying will not be tolerated, and will be treated as a violation of the NSEES honor code. Late work will not be accepted.

Students requesting regrades must make these requests within one week of receiving the graded material. Attach a note explaining the regrade issue to your homework or exam and submit to instructor. The instructor or TA has the option to regrade the entire homework or exam.

Some guidelines for submitting written material:

• Written interpretations and conclusions are at least as important if not more important than generation of data summaries, statistics, tests, etc. Clear, careful writing and interpretation of results is an important part of the homework, midterms, project and final exam.

• Unless specifically requested, never submit raw computer output pages. Figures should be properly sized and integrated into reports with captions. Instead use a text editor to cut and paste parts of the output file into your writeup. Output, plots, variables, etc. should be labeled appropriately.

Grading Scheme:

• Weekly homework/On-line quizzes: 20%
• Written assignments: 20%
• Midterm 1: 10%; Midterm 2: 10%
• Final Project: 20%
• Final Exam: 20%

Software: S-Plus Version 6 for Windows, Insightful, Inc.

Students enrolled in the course can obtain the software at no charge via download from the OIT website or may purchase a CD for $15.

You will be asked to turn in reports using a word processor with an equation editor. If you use Microsoft Word, you can reinstall the software, select "custom" and install the Word Equation Editor add-on. Other equation editor programs such as MathType can be used in conjunction with Word.