Syllabus of Preventive Medicine 650, section 2

Introduction to Quantitative Methods-Population Health

Fall 2001

 

Instructor: Dr. Guan-Hua Huang 

Office: 703 WARF

Office phone: 608-265-6176

Email: guanhuahuang@facstaff.wisc.edu

Course website: http://webct.wisc.edu/

Credit: one (1) credit independent study

Class meetings: Tuesday from 2:30 to 3:30 at 758 WARF

Office hours: generally available following class, or by appointment

 

COURSE SUMMARY

 

The goals of the class are to introduce and develop skills in using the SAS statistical package, and to illustrate statistical concepts through the help of SAS. This class also intends to provide the bridge between Statistics 541 (Introduction to Biostatistics) and Population Health 800 (Quantitative Methods in Population Health I). In the class, we will cover

 

 

The course schedule will be closely related to Statistics 541. Therefore, students are expected to be well prepared about the course material of Statistics 541.

 

HANDOUTS AND RECOMMENDED TEXTS

 

Handouts corresponding to each lecture will be available on the course website before each class. While there are no required texts, it is good to have some SAS reference books. I find the following texts quite helpful:

 

 

INTENDED AUDIENCE

 

The course will be of interest to master’s and Ph.D. students in population health sciences who are taking (or have taken) Statistics 541 and will also take Preventive Medicine 800.

 

METHOD OF STUDENT EVALUATION

 

The course grade will be based upon analyzing a provided data set.  Each student is required to write a 10 pages or less (including all the texts, tables and graphics) scientific report of the analysis methods and results. The detail format of the report will be given in class.

 

COURSE OUTLINE (may be subject to some modification during the semester)

 

Lecture 1 (9/4)

Introduction to SAS, including manipulating data in SAS, creating the temporary and permanent SAS data sets, and basic SAS programming.

Lecture 2 (9/11)

Introduction to SAS continued.

Lecture 3 (9/18)

Explore and graphically display data.

Lecture 4 (9/25)

SAS procedures for data exploration.

Lecture 5 (10/2)

Modify and combine SAS data sets.

Lecture 6 (10/9)

Random numbers and probability distributions in SAS.

Lecture 7 (10/16)

Advanced SAS programming.

Lecture 8 (10/23)

SAS macro.

Lecture 9 (10/30)

SAS procedures for hypothesis testing, including one-sample, two-sample and paired t-tests.

Lecture 10 (11/6)

Prevalence, incidence, relative risk, odds ratio and Kappa statistics.

Lecture 11 (11/13)

SAS procedures for analyzing categorical data, including Chi-square test, and tests for homogeneity and agreement.

Lecture 12 (11/20)

SAS graph and output delivery system (ODS)

Lecture 13 (11/27)

SAS procedures for regression analysis.

Lecture 14 (12/4)

SAS procedures for nonparametric methods.

Lecture 15 (12/11)

Where to go from here.