Course Website Locator: bio213-01

Harvard School of Public Health

The following course websites match your request:

Fall 2009

Dr. E. J. Orav
5 credits
Lectures. Two 2-hour sessions each week. One 1.5-hour lab each week.

This course will introduce students involved with clinical research to the practical application of multiple regression analysis. Linear regression, logistic regression and proportional hazards survival models will be covered, as well as general concepts in model selection, goodness-of-fit, and testing procedures. Each lecture will be accompanied by a data analysis using SAS and a classroom discussion of the results. The course will introduce, but will not attempt to develop the underlying likelihood theory. Background in SAS programming ability required.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

Fall 2008

Dr. E. J. Orav
5 credits
Lectures. Two 2-hour sessions each week. One 1.5-hour lab each week.

This course will introduce students involved with clinical research to the practical application of multiple regression analysis. Linear regression, logistic regression and proportional hazards survival models will be covered, as well as general concepts in model selection, goodness-of-fit, and testing procedures. Each lecture will be accompanied by a data analysis using SAS and a classroom discussion of the results. The course will introduce, but will not attempt to develop the underlying likelihood theory. Background in SAS programming ability required.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

Fall 2007

Dr. E. J. Orav
5 credits
Lectures. Two 2-hour sessions each week. One 1.5-hour lab each week.

This course will introduce students involved with clinical research to the practical application of multiple regression analysis. Linear regression, logistic regression and proportional hazards survival models will be covered, as well as general concepts in model selection, goodness-of-fit, and testing procedures. Each lecture will be accompanied by a data analysis using SAS and a classroom discussion of the results. The course will introduce, but will not attempt to develop the underlying likelihood theory. Background in SAS programming ability required.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

Fall 2006

Dr. E. J. Orav
5 credits
Lectures. Two 2-hour sessions each week. One 1.5-hour lab each week.

This course will introduce students involved with clinical research to the practical application of multiple regression analysis. Linear regression, logistic regression and proportional hazards survival models will be covered, as well as general concepts in model selection, goodness-of-fit, and testing procedures. Each lecture will be accompanied by a data analysis using SAS and a classroom discussion of the results. The course will introduce, but will not attempt to develop the underlying likelihood theory. Background in SAS programming ability required.
Course Note: BIO 200, or BIO 201, or BIO 202 and BIO 203, or BIO 206 and one of BIO 207, BIO 208, or BIO 209, or signature of instructor required; lab or section times to be announced at first meeting. (5.06)

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

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