School of Public Health
If you're right 90% of the time, why worry about the remaining 3% ? - Unknown.
The intent in this course is to gain some skill in statistical computing using SAS, Splus, and possibly FORTRAN or C. The recurring theme is solving problems by turning an algorithm into a program that provides relevant answers. Some background in probability and statistics, including an introduction to likelihood, is needed.
Topics covered will include use of pseudo-random number generators, distribution functions (pdfs and cdfs), matrix manipulations with applications to regression and estimation of variance, simulation studies, minimization of functions using various algorithms, nonlinear regression, manipulation and combination of datasets, techniques of macro programming, and methods of integration using quadrature.
The course is intended primarily for MS and MPH students in Biostatistics and Statistics. At least one previous semester of courses in biostatistics and statistics and concurrent or previous enrollment in a course involving linear regression are strongly recommended.
The main content of the course is a series of computing projects (see Syllabus). Datasets based on previous studies will be available for providing examples of computational methods.
This course is not intended as a continuation of SPH 5420. In general the level of statistical knowledge and mathematical skill is somewhat advanced over that required in SPH 5420 or the SPH 5450-5452 sequence.
Notes for this course:
Web address of this page: http://www.biostat.umn.edu/~john-c/ph5421.s2003.html
Most recent update: September 1, 2003.
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