Degree Programs. Introduction to the theory of probability, with emphasis on applications in computer science. Introduction to statistics and its connection to all stages of the scientific inquiry process. Model assumptions. A variety of applications taken from some of the following areas are discussed in the context of stochastic modeling: Information Theory, Quantum Mechanics, Statistical Analyses of Stochastic Processes, Population Growth Models, Reliability, Queuing Models, Stochastic Calculus, Simulation (Monte Carlo Methods). An overview of theory and methods in the analysis of survival data. This program gives students a broad understanding of the methods and computational and communication skills appropriate for effective statistical problem solving. Variational autoencoders and generative adversarial networks. endobj
Enrolment instructions can be found on the Arts & Science Program Toolkit website. We would like to show you a description here but the site won’t allow us. Pittsburgh, PA 15213 For students who have completed 9.0 or more credits: • CSC108H1/ CSC120H1/ CSC148H1• MAT223H1/ MAT240H1• MAT235Y1/ MAT237Y1/ MAT257Y1• ( STA237H1 and STA238H1) with a minimum grade of 75% in each/ ( STA247H1 and STA248H1) with a minimum grade of 75% in each/ ( STA257H1 and STA261H1) with a minimum grade of 65% in each. Note: Students who take ( STA237H1, STA238H1)/( STA247H1, STA248H1) will typically require a higher minimum grade average than students who take ( STA257H1, STA261H1). Other courses may qualify as well; consult with the Statistics Undergraduate Advisor. 2.0 credits from the following list, including at least 1.0 credit at the 400 level (see below for additional conditions): Students in the Focus in Evolutionary Biology can request that HMB waive the co-requisite of. K. Knight, M Sc, Ph D Recommended: introductory course in disciplinary focus. 2. This course is restricted to students in the Data Science Specialist program. STA130H1, CSC108H1/ CSC120H1/ CSC148H1, ( MAT135H1, MAT136H1)/ MAT137Y1/ MAT157Y1. N. Taback, B Sc, M Sc, Ph D, Assistant Professors, Teaching Stream Suggestions for further research which would enhance the validity of this area of research are Beyond the information provided here, we encourage interested students to meet with an undergraduate advisor. McMaster University’s Undergraduate and Graduate Calendars are its official repository for degree, program, and course requirements, along with the rules, regulations, policies, fees, and information about financial aid and scholarships. Continuation of STA220H1 (or similar course), emphasizing major methods of data analysis such as analysis of variance for one factor and multiple factor designs, regression models, categorical and non-parametric methods (Note: STA221H1 does not count as a distribution requirement course). Least squares estimation and inference for non-linear regression. 21-127 : Concepts of Mathematics Note: Students planning to take any of these courses should ensure they have the required prerequisites. Calendar; Resources; Contact Us; Search form. Statistical Science encompasses methods and tools for obtaining knowledge from data and for understanding the uncertainty associated with this knowledge. For students admitted to other Arts & Science Year 1 admission categories: Variable Minimum Grade Bayesian inference has become an important applied technique and is especially valued to solve complex problems. Topics of current research interest are covered. Singapore's National Statistical Office that collects, compiles and disseminates economic and socio-demographic statistics. M. Alexander, B Sc, MA, MSR, Ph D Details at https://www.artsci.utoronto.ca/current/academics/research-opportunities/research-opportunities-program. The statistics course offerings are intended not only for students in statistics programs of study, but also to serve the needs of the many other disciplines that use statistical methods. Statisticians and data scientists are involved in solving problems as diverse as understanding the health risk of climate change, predicting the path of forest fires, understanding the role of genetics in human health, and creating a better search engine. Statistics. Examples of such areas will be provided to students by program advisors and will form the basis for a later proposal for program Focuses (to be approved through internal Arts & Science governance procedures). Factorial designs. 1.0 credit from the following list: MAT224H1/ MAT247H1, MAT337H1/ MAT357H1, CSC148H1, CSC207H1, STA300+ level courses (excluding STA310H5). © 2020 Faculty of Arts & Science, University of Toronto, https://www.artsci.utoronto.ca/current/academics/research-opportunities/research-opportunities-program, https://www.artsci.utoronto.ca/current/academics/research-opportunities/research-excursions-program. For Current Students, Carnegie Mellon One of STA492H1, STA496H1/ STA497H1/ STA498Y1/ STA499Y1 or successful completion of an internship involving Statistics when an internship program becomes available. Examples illustrating statistical theory and its limitations. N.M. Reid, M Sc, Ph D, FRSC, OC, Professors These topics will be explored through case studies and collaboration with researchers in other fields. Overview; MS in Statistics Degree. Data science workflows will be integrated throughout the course. Lin, M Sc, Ph D, ASA Class of 2010 histogram. This requirement is a prerequisite for the course 36-401. If you take CSC240H1 without CSC165H1, there is no need to replace the missing half-credit for program completion; however, please base your course choice on what you are ready to take, not on "saving" a half-credit. Students admitted to the program after second or third year will be required to pay retroactive deregulated program fees.