Statistics Designated Emphasis
Introduction
Students from a Ph.D. degree program, other than statistical science, who meet the following requirements can have the designated emphasis of “statistics” annotated to their degree title. For example, a Ph.D. student in electrical engineering who meets the requirements would receive a dioploma that reads “Ph.D. Electrical Engineering with an emphasis in (Statistics).”
Requirements
Committee Composition and Departmental Approvals
Upon electing to pursue a designated emphasis (DE) in statistics, students must choose a DE faculty adviser in the Statistics Department. A list of eligible DE advisers is maintained online. The student must organize a preliminary meeting with the DE adviser, and agree on a plan for completion of the requirements. Once this plan has been designated, the student and the DE adviser must complete the Application for a Designated Emphasis in Statistics form. The completed application form should be signed by the student's home department adviser, the DE adviser, and the statistics graduate director, and then filed with the BSOE Graduate Student Affairs Office (bsoe-ga@rt.ucsc.edu). This should be done before the student's advancement to candidacy (for Ph.D. students).
Course Requirements
Both these courses
STAT203 | Introduction to Probability Theory | 5 |
STAT207 | Intermediate Bayesian Statistical Modeling | 5 |
Plus one of these courses
STAT206 | Applied Bayesian Statistics | 5 |
STAT206B | Intermediate Bayesian Inference | 5 |
Plus one other statistics course from the following list of approved courses
STAT204 | Introduction to Statistical Data Analysis | 5 |
STAT205 | Introduction to Classical Statistical Learning | 5 |
STAT205B | Intermediate Classical Inference | 5 |
STAT208 | Linear Statistical Models | 5 |
STAT209 | Generalized Linear Models | 5 |
STAT222 | Bayesian Nonparametric Methods | 5 |
STAT223 | Time Series Analysis | 5 |
STAT225 | Multivariate Statistical Methods | 5 |
STAT226 | Spatial Statistics | 5 |
STAT229 | Advanced Bayesian Computation | 5 |
STAT243 | Stochastic Processes | 5 |
STAT244 | Bayesian Decision Theory | 5 |
STAT246 | Probability Theory with Markov Chains | 5 |
STAT291 | Advanced Topics in Bayesian Statistics | 3 |