Course Home | Handouts | Assignments | Data | Computing | Course Info | Duke Statistics Home | Duke Home

Instructor: Merlise Clyde
Office: 223 E Old Chemistry Building	Office hours: by appointment
Phone: 681-8440	Email: clyde@stat.duke.edu
Lecture:: 025 Old Chemistry Building 01 Old Chemistry (Time Change) .	Tuesday 12:40-1:55 Tuesday 4:00-5:15

 

This course provides a broad introduction to a range of topics in statistical science and data analysis. Topics will be selected from:

• data types and data manipulation using data sets from a variety of application fields
• exploratory data analysis and statistical graphics
• models for binary and count/categorical data and regression models
• elements of statistical inference using probability models, including basic issues of sampling-theory and Bayesian inference
• modeling "related" phenomena through the notion of hierarchical models
• statistical and mathematical techniques including elements of simulation and linear/matrix algebra useful in statistics
• programming environments such as R/S-Plus
• use of unix tools, including emacs and LaTeX

Though the course does not include rigourous development of statistical theory and methods, we will use and review various concepts and methods of inference, so that some familiarity with basic statistics is desirable. Co-registration in STA 213 or recent experience with similar courses will be most useful. While no texts are required, students may find the following list of references useful.

Grading will be based on classroom presentations, homework, and takehome exams (midterm and final)