Statistics is concerned with drawing conclusions and making decisions from empirical data. Mathematical modeling plays an important role in statistics, with a special role for probability theory, which is often used to describe the variations in observed data and as a basis for making inferences from them. The computer is also an essential tool; it enables us to analyze and visualize increasingly complex data sets.
Modern Statistics covers a wide range of disciplines from the theoretical development of complex statistical and stochastic models to the most advanced applications of statistical methods in engineering, industry, medicine, biology, economics, social sciences and other fields. Typical problems range from efforts to identify risk factors for heart disease to design and analysis of an experiment to improve a production process to testing the effect of a new instructional program to estimating indices for tracking the economy. There is a strong interplay in statistics between theory and practice and many important ideas arose from the need to solve real problems. Statistical methods are needed in virtually all branches of science and technology and one of the exciting and enjoyable aspects of statistics is the opportunity to collaborate with colleagues from many different areas.
Biostatistics deals with development and applications of statistical tools in biology, medicine and public health. Its role is essential in such areas as the design and analysis of clinical trials in medical and pharmaceutical research, the detection of influential genes, and the search for enviromental factors affecting various deseases in epidemiological studies. Biostatistical methods are widely used in modern genetics and bioinformatics. The multi-displinary nature of biostatistics requires a close collaboration with colleagues from other fields and makes it necessary to understand the problems they are facing. In additon to providing students with necessary statistical tools, the Biostatistics program involves basic epidemiological and medical science studies given by the Faculty of Medicine at Tel Aviv University.
The Department of Statistics & Operations Research offers three M.Sc. degrees in Statistics: Statistics & Probability, Applied Statistics and Biostatistics. The normal requirement for admission as a M.Sc. student for all degrees is a strong undergraduate record in Statistics, Mathematics or a related subject. The Biostatistics program also welcomes applicants with degrees in Life Science or Medical Science and strong mathematical ability. The usual period of full-time study for the M.Sc. is two years to complete courses and an additional half a year - a year to finish the M.Sc. Thesis. During the studies a student has to take 30 credit hours of courses. Advanced courses for Graduate Students usually give 3 credit hours. To finish the degree one must carry out a research project under the supervision of one of the staff members of the Department you can choose and, as a result, to submit the M.Sc. Thesis.
There are four mandatory courses in Applied Statistics (Advanced Statistical Theory, Selected Topics in Mathematics for Statistians, Statistical Laboratory Workshop and a statistical seminar for graduate students) and four for Statistics & Probability (Advanced Probability, Advanced Statistical Theory, two advanced seminars for graduate students), while others can be chosen from a variety of elective courses covering a wide spectrum of topics in statistics and probability. Students are also encouraged to take courses in related areas such as Operations Research, Mathematics, Computer Science.
For Biostatistics program a student has to take at least 18 credit hours from the Department of Statistics & OR and at least 10 from the Faculty of Medicine. The required courses include Statistical Theory,Regression, Experimental Design and Analysis of Variance,Analysis of Contingency Tables, Survival Analysis, Statistical Laboratory Workshop and a statistical seminar for graduate students within Department of Statistics & Operations Research, and Introduction to Epidemiology and Methods in Research & Surveys within the Department of Epidemiology. Students that already took these courses during their undergraduate studies will complete the credit hours by other advanced statistical/epidemiological courses. Students without corresponding background in statistics and epidemiology will be required to complete Probability, Introduction to Biochemistry and Introduction to Physiology & Pathalogy without credit. The required background in mathematics for Biostatistics program includes two semesters of calculus and one semester of linear algebra.
More details about the programs may be found on the Yedion or consulting with an Advisor for Graduate Students in Statistics who will be happy to help you in compiling your study program which will suit your interests and needs.
The usual period of full-time study for the M.Sc. in Operations Research is two years to complete the course work and an additional year to finish the M.Sc. Thesis. A student has to take 30 credit hours of courses, where advanced courses for graduate students usually give 3 credit hours each. There are five mandatory courses in the program (Convex Analysis & Optimization, Queuing Theory, Network Flows, one out of the 3 courses: Location, Integer Programming and Dynamic Programming, and an advanced seminar for graduate students), while other courses can be selected from a variety of elective courses offered by the Department. Students are also encouraged to select courses in related areas such as Applied Statistics, Probability, Computer Science and Mathematics. To complete the requirements and graduate, the student must carry out a research project under the supervision of one of the staff members of the Department , and submit the M.Sc. Thesis.
Information about the Department of Statistics & Operations Research can be obtained here .