Areas of Specialization
With the approval of the Ontario Council of Graduate Studies, students in the Master Program in Statistics have the opportunity to specialize in the areas of:
- Medical Statistics (Biostatistics)
- Applied Statistics
- Statistical Theory
- Applied Probability
A variety of elective courses will be available to cater to individual interests. All students will be required to complete core courses on the foundations of statistics. Students interested in a particular application area may receive graduate credit for certain courses given in other departments.
Although a student with a good undergraduate background in statistics should be able to complete the requirements for the M.Sc. degree in one calendar year of study, it is expected that some students will require longer. Students entering the program after receiving an undergraduate degree in science or engineering with minimal preparation in statistics may be required to take some background courses. Students with a good undergraduate background in statistics may want to study statistics as applied to a particular application area. These students will be required to take courses outside of statistics to become familiar with the application area of interest. For example, a program in medical statistics would involve taking courses in health research methodology. Students will also be expected to develop their report-writing and presentation skills and become familiar with the use of statistical packages on microcomputers and workstations.
The particular areas of specialization to be emphasized in the program will be those in which the faculty members have special expertise. Statistics faculty drawn from five different faculties and schools make this program uniquely interdisciplinary. Since several of the faculty are biostatisticians in the Health Sciences Centre, one of the major areas will be health and medical statistics. Students specializing in this area will learn the various issues involved in the conduct of large multi-centre clinical trials, and the methods for analyzing survival data and multi-dimensional contingency tables. These students will interact closely with their peers enrolled in the Health Research Methodology Program, and will take courses in medical sciences. Through thesis work supervised by members of the biostatistics faculty, they will have opportunities to gain experience in statistical consulting in a health sciences context.
Students who do not wish to specialize exclusively in health and medical statistics, but rather in a broader area of applied or theoretical statistics, may obtain training in one or more of the following areas: environmetrics, time series analysis, stochastic models in biology, statistical methods in genetics, economics, nonlinear models, applied statistics, order statistics, reliability, analysis of censored data, the booststrap and other resampling methods, non-parametric methods, comparative inference, and quality control. Our Research Data Centre, a Statistics Canada unit at McMaster, holds large real-life data sets from longitudinal surveys that are suitable for statistical analyses for theses and other research projects. Students interested in business or industrial applications may arrange to do their thesis work off-campus. Those interested in combining statistics with financial mathematics can take courses offered by the PhiMac Group at McMaster.
The Graduate Program in Statistics is subject to all existing University regulations and specifically to the general regulations governing Master’s degrees as established by the School of Graduate Studies and set out near the front of this Calendar. Either a full-time or a part-time program of study may be undertaken.
A. Admission Standards
B.A. or B.Sc. honours degree, B+ standing, or equivalent, with a good background in statistics and mathematics. Students with a degree in engineering, science, health sciences, or social sciences will enthusiastically be considered, provided they have a B+ average with sufficient mathematics and statistics background. Students coming from other areas may be required to take additional undergraduate courses to make up any deficiencies.
For those in the Thesis Option, a thesis will typically be 50 to 150 pages in length, exclusive of tables, graphs and appendices, written and bound in the usual format for a thesis. Standard statistical analyses applied to a novel application, or original contributions to statistical methodology with adequate presentation of background material will be acceptable thesis work. Students will be required to defend their theses orally.