|Instructor||Dr. James Hanley|
|Co-ordinates||tel: (514) 398-6270
|Overview||The course covers the elementary statistical principles and methods used in data-analysis in scientific and population-health research, and the theoretical (mathematical-statistics) foundations for these methods. The applications illustrated will be drawn mainly from epidemiologic and clinical research; portions of the classes and assignments will involve mathematical statistics; others will require some statistical computing.|
|Target||This course is aimed at MSc and PhD students in the department's biostatistics program, i.e., students with undergraduate training in mathematical statistics who are interested in the application of statistical methods to epidemiologic, biomedical and other biological research. However the skills and understanding acquired in this course are also applicable to other fields of research that use quantitative methods. Statistically-prepared students from other departments or universities are especially welcome.|
|Topics||1a: Epidemiologic concepts, terminology and measures.
1b: Surveys, sampling, and measurement
1c: Statistical models, inference and planning for such (1-sample) studies.
2a: Comparative studies [experimental, non-experimental, quasi-experimental]
-- in general
-- specifically in epidemiology (with associated terminology and measures).
2b: Statistical models, inference and planning for comparative studies.
3: Study designs & statistical methods for reducing bias & increasing precision.
It is assumed that students will have already encountered the basic statistical models
(Gaussian, Binomial and Poisson random variables) and basic inferential procedures.
The distinguishing features will be the
|When||Mondays and Wednesdays 13:30-15:30. first/last class: Sept 4/Dec 3.
|Where||Room 24, first Floor, Purvis Hall, 1020 Pine Ave. West [corner Pine]|
|Prerequisites||Undergraduate course in mathematical statistics at level of MATH 324, or permission of instructor.|
|No. of Credits||4|
|Assessment|| To be discussed at first class: suggested:- assignments [xx%], participation [xx%], exams[xx%]
McGill University Senate resolution of January 29, 2003 on academic integrity...
McGill University values academic integrity. Therefore all students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Code of Student Conduct and Disciplinary Procedures. For more details, consult the link below.
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