The curriculum consists of a thesis that incorporates a research proposal, an oral defense (viva voce) and two manuscripts, based on the candidate's research, submitted for publication to a recognized accredited journal. Proof of the submission of the manuscripts is a compulsory condition for the degree to be conferred.

Statistics and operations research are today of great importance as part of mathematics and as necessary disciplines for the understanding and advancement of other branches such as Economics, Engineering or Medicine, among others.

The Department of Statistical Science began offering a Ph.D. in Statistical Science in 1968. Since that time it has awarded over 185 Ph.D. degrees. The courses in the Ph.D. curriculum in Statistical Science at SMU provide our students with the strong theoretical foundation in mathematics, statistical inference, and probability needed for students pursuing a research-oriented Ph.D. degree.

The PhD program in "Mathematics, Computer Science, Statistics", based in Firenze, is managed by a Consortium among the University of Firenze, the University of Perugia and the Istituto Nazionale di Alta Matematica "F. Severi"-Rome (INdAM). This PhD program inherited the tradition of the pre-existing three separate PhD's in Mathematics, Computer Science, Statistics, and can rely upon the very many, and well established, scientific connections of the involved institutions with Universities and Research Centers in many Countries of the World. The relevant number of offered scholarships allows the achievement of a critical mass of PhD students and activities, which are fundamental for a doctorate with an interdisciplinary character.

The purpose of the Ph.D. in Mathematical Statistics is to provide qualifying students with an in-depth understanding and integrated knowledge of advanced applicable theory in the field of mathematical statistics.

CERGE-EI (Center for Economic Research and Graduate Education - Economics Institute) is a joint workplace of Charles University and the Economics Institute of the Czech Academy of Sciences.

Excellence in advanced training Applied Mathematics, through research work on the theme of the frontier of athematical knowledge; Solid and deep scientific knowledge in the area of Ap. Mathematics to enrich the previous training of the student; Maturity of logical and abstract reasoning; - Independence and creativity in problem solving in mathematics and its applications; - Innovation in treating problems of mathematics and applications to other contexts. We have a PhD program in Applied Mathematics that pools the considerable human and material resources of the participating institutions, to provide a research based degree, internationally competitive, in such areas as Analysis and Optimization, Statistics and Probability, Dynamics and Geometry and Algebra, Logic and Computation. Also our curricular component is sufficiently flexible to accommodate the varied interests and backgrounds of potential students, and it is also useful for the development of specific and transverse skills

A candidate must complete a thesis in one of several fields in which research is actively being done in the Department.

Nowadays, science and technology are rapidly developing with an ever-increasing impetus and a substantial part of knowledge is comprised of quantitative data. The analysis and interpretation of this data require the use of mathematical and statistical methods.

The aim of the Ph.D. Course in Mathematical Analysis, Modelling, and Applications is to educate graduate students in the fields of mathematical analysis and mathematical modeling, and in the applications of mathematical and numerical analysis to science and technology.

Students who complete the PhD program will gain knowledge in probability, statistical inference, and hypothesis testing, the design and conduct of experimental and epidemiological studies, statistical computation, and data analysis.

This program prepares students for the proper use and application of advanced statistics and evaluation procedures, specifically applied in the social and behavioral disciplines of education, psychology, counseling and other related fields. Our graduates are prepared for educational research and evaluation positions in schools, government agencies, private corporations and foundations, colleges and universities, research institutions and national testing centers.

The Ph.D. program will produce biostatisticians who can develop a biostatistical methodology that can be utilized to solve problems in public health and the biomedical sciences. In addition, graduates of the Ph.D. program will be prepared to apply biostatistical and epidemiology methodology for the design and analysis of public health and biomedical research investigations. Finally, graduates of the Ph.D. program will be well suited to function as collaborators or team leaders on research projects in the biomedical and public health sciences. The program requires competency in the theory of statistics and probability, in introductory and advanced biostatistical methods and theory, and in fundamentals of epidemiologic study design. The doctoral dissertation will be the culminating experience in the Ph.D. program. Graduates of the doctoral program will have written a doctoral dissertation that focuses on the development of a new methodology or on the innovative application of biostatistical methods to a health sciences research problem. Graduates of the Ph.D. program will be in a position to: Demonstrate an increased level of knowledge and understanding of current statistical theory, methods, and practices in the health sciences. Develop new statistical methods. Design, manage data, analyze and interpret data from a variety of experimental and observational studies. Communicate research findings, including new statistical methods developed, effectively to various audiences in writing and through oral presentation The goals of the Ph.D. program are to train students in the application of appropriate statistical methods for diverse problems in medicine and public health and to provide a solid theoretical foundation for the development and investigation of new statistical methods. In addition to the formal statistical training, students will have adequate flexibility in choosing statistical and non-statistical electives to tailor their curriculum towards a specific application area such as genetics, epidemiology, or environmental health.

Wharton’s Ph.D. program in Statistics allows students to engage in both cutting-edge theories and applied problems. These include problems from a wide variety of fields within Wharton, such as finance, marketing, and public policy, as well as fields across Penn such as biostatistics within the Medical School and computer science within the Engineering School.

Statistics as a discipline develops methods to collect and interpret data. Modern statistical methods are used in many areas, such as medicine, the biological and social sciences, economics, finance, manufacturing, marketing research, management, government, and research institutes.