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Course Catalog


Department: Biostatistics
Term: Winter I term
Credits: 2 credits
Contact: Judy Holzer
Academic Year: 2012 - 2013
Course Instructor:

Covers methods for the organization, management, exploration, and statistical inference from data derived from multivariable regression models, including linear, logistic, Poisson and Cox regression models. Students apply these concepts to two or three public health data sets in a computer laboratory setting using STATA statistical software. Topics covered include generalized linear models, product-limit (Kaplan-Meier) estimation, Cox proportional hazards model.

Learning Objective(s):
Upon successfully completing this course, students will be able to:
Conduct a simple linear, logistic or survival regression and correctly interpret the regression coefficients and their confidence interval
Conduct a multiple linear, logistic or survival regression and correctly interpret the coefficients and their confidence intervals
Examine residuals and adjusted variable plots for inconsistencies between the regression model and patterns in the data and for outliers and high leverage observations
Fit and compare different models to explore the association between outcome and predictor variables in an observational study.

Methods of Assessment: quizzes and final exam
Location: East Baltimore
Enrollment Minimum: 10
Enrollment Maximum: 25
Enrollment Restriction: Pacific Rim DrPH students ONLY
Instructor Consent: Consent required for all students

All students must receive consent from Judy Holzer to register for this section only

For consent, contact:

Data Analysis Workshop I and II (140.613 and 140.614)

Auditors Allowed: No
Grading Restriction: Letter Grade or Pass/Fail
Frequency Schedule: One Year Only
Next Offered: 2015-2016