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 advisor in the Statistics Department. A list of eligible DE advisors is maintained online. The student must organize a preliminary meeting with the DE advisor, and agree on a plan for completion of the requirements. Once this plan has been designated, the student and the DE advisor must complete the Application for a Designated Emphasis in Statistics form. The completed application form should be signed by the student's home department advisor, the DE advisor, 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
| STAT 203 | Introduction to Probability Theory | 5 |
| STAT 207 | Intermediate Bayesian Statistical Modeling | 5 |
Plus one of these courses
Plus one other statistics course from the following list of approved courses
| STAT 204 | Introduction to Statistical Data Analysis | 5 |
| STAT 205 | Introduction to Classical Statistical Learning | 5 |
| STAT 205B | Intermediate Classical Inference | 5 |
| STAT 208 | Linear Statistical Models | 5 |
| STAT 209 | Generalized Linear Models | 5 |
| STAT 222 | Bayesian Nonparametric Methods | 5 |
| STAT 223 | Time Series Analysis | 5 |
| STAT 225 | Multivariate Statistical Methods | 5 |
| STAT 226 | Spatial Statistics | 5 |
| STAT 227 | Statistical Learning and High Dimensional Data Analysis | 5 |
| STAT 229 | Advanced Bayesian Computation | 5 |
| STAT 243 | Stochastic Processes | 5 |
| STAT 244 | Bayesian Decision Theory | 5 |
| STAT 246 | Probability Theory with Markov Chains | 5 |
| STAT 291 | Advanced Topics in Bayesian Statistics | 3 |