STA 213
Introduction to Statistical Methods
Syllabus
Duke University
Fall 2004
MW 2:50-405
101 Old Chemistry Building
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Instructor:
| Michael Lavine
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|---|
| Office: 218 Old Chemistry Building |
| Phone: 684-2152 |
| Email: michael@stat.duke.edu |
Office Hours: by appointment or drop in
Teaching Assistant:
|
Name
|
Email
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Phone
|
Office Hours
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Office Location
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|---|
| Natesh Pillai | natesh@stat.duke.edu |
684-4558 | | 214 Old Chem |
The Course:
There are two required texts. The first is Statistics, written by me and available for
free download as a pdf file. The book has been only partially
written. Expect mistakes and omissions. Please help me improve it
during the semester. The second required text is Statistical
Inference by George Casella and Roger Berger. The second text
contains more mathematical details than the first. Those of you who
plan to take subsequent courses in ISDS should become familiar with
the details in the second text. I plan to cover Chapters 1, 2, 5 and
6 of Statistics which correspond roughly to Chapters 2-7 of
Statistical Inference.
We will take both a theoretical and a computational approach.
Calculus will be important. I will write down integrals and
derivatives and expect you to know what they mean. We will also use
the computer software R which is on the ISDS computers, the
Duke computers, and is available for free download at http://www.r-project.org/.
Using R will not only give you familiarity with a statistics
package; it will help you learn the theory better.
I hope you will feel free to talk to me anytime about the class,
either with questions about the material or with comments about the text
or the way the course is conducted.
Assignments and Grading:
There will be weekly quizzes and homeworks plus a final exam.
From the homework problems assigned each week I will select one to be
graded. You may discuss homework problems together, but when you
write them up the work must be your own. You should not derive a
solution together and then merely copy it. You may work together to
the point of understanding a problem. But when you write it up the
language must be your won and should flow from your understanding of
the problem. Grades will be based on all three components ---
homework, quizzes and final. To get an "E" you must do well on all
three parts.
Advice:
Read the book. Work lots of problems. Write code in R.
Write clearly, succintly and to the point. Work lots of problems.
Write code in R. Discuss with your colleagues. Work lots of
problems. Write code in R.
course homepage
course schedule
Homework solutions
Last updated Aug. 30, 2000 by Michael Lavine