The Department of Biostatistics and Computational Biology at the University of Rochester conducts teaching and research in statistical theory and methodology oriented toward the health sciences. Our unique graduate program is located within a School of Medicine environment and provides many opportunities for stimulating interaction with applied research.<br>The department interprets the term statistics very broadly, with specialization available in probability, statistical theory and analysis, biostatistics, and interdisciplinary areas of application. Department faculty participate fully in graduate teaching and individual attention is given to each student through intensive advising, extensive small seminars, and research collaboration. Students have opportunities for supervised teaching and statistical consulting experience. Prior to completing their degrees, most Ph.D. students have several publications underway based on research done in collaboration with faculty members in biostatistics/statistics and in various medical departments.<br>The Master of Arts (MA) degree in Statistics requires satisfactory completion of at least 32 credits and a final comprehensive written examination, no thesis is required. Of the 32 credits, at least 24 must be in departmental courses primarily at the 400 level or above.<br>A typical program for the MA consists of PhD-level courses taken in Semesters 1 (three courses), 2 (three courses), and 3 (two courses), however, MA students have the option of completing the program in two semesters (four courses per semester). A balanced program is worked out with the student's advisor. The final comprehensive examination is administered during the summer following completion of the first year of study.<br>The requirements for entry into the MA program in Statistics are the same as those for entry into the Statistics PhD program. Entering MA students should have a strong background in mathematics, including three semesters of calculus (through multivariable calculus), a course in linear and/or matrix algebra, and a year of probability and mathematical statistics. A course in real analysis is encouraged, a course in statistical methods is also recommended.