For admission for an Option A Minor in statistics, the candidate must have had at least one year of calculus, and an introductory knowledge of statistics that is satisfactory to the department. Any of the following (or an equivalent course) is sufficient for this purpose:
| Code | Title | Credits |
|---|---|---|
| STAT 240 | Data Science Modeling I | 4 |
| STAT 301 | Introduction to Statistical Methods | 3 |
| STAT 302 | Accelerated Introduction to Statistical Methods | 3 |
| STAT 324 | Introductory Applied Statistics for Engineers | 3 |
| STAT 371 | Introductory Applied Statistics for the Life Sciences | 3 |
| STAT/B M I 541 | Introduction to Biostatistics | 3 |
| STAT/F&W ECOL/HORT 571 | Statistical Methods for Bioscience I | 4 |
GENERAL REQUIREMENTS FOR AN OPTION-A MINOR IN STATISTICS FOR GRADUATES:
Please carefully read the requirements below. Requests for further information should be addressed to the PhD Minor Advisor in the Department of Statistics. Note: Candidates for an Option A Minor in Statistics must be aware of the Graduate School "Minors" policy. For further information please visit this link: https://stat.wisc.edu/statistics-doctoral-minor/
The student should have a program of study approved by the PhD Minor Advisor in the Department of Statistics and the student's major advisor, early in the student's graduate work. The proposed program should be submitted to and approved by the minor program advisor in statistics upon, or before, the completion of 6 credits.
| Code | Title | Credits |
|---|---|---|
| Students must take at least four courses totaling 12 or more credits from the following lists: | ||
| List 1 (at least one course): | ||
| STAT 303 | R for Statistics I | 1 |
| STAT 304 | R for Statistics II | 1 |
| STAT 305 | R for Statistics III | 1 |
| STAT 327 | Learning a Statistical Language | 1 |
| STAT 333 | Applied Regression Analysis | 3 |
| STAT 340 | Data Science Modeling II | 4 |
| STAT 349 | Introduction to Time Series | 3 |
| STAT 351 | Introductory Nonparametric Statistics | 3 |
| STAT 411 | An Introduction to Sample Survey Theory and Methods | 3 |
| STAT 421 | Applied Categorical Data Analysis | 3 |
| STAT/M E 424 | Statistical Experimental Design | 3 |
| STAT 433 | Data Science with R | 3 |
| STAT 443 | Classification and Regression Trees | 3 |
| STAT 451 | Introduction to Machine Learning and Statistical Pattern Classification | 3 |
| STAT 453 | Introduction to Deep Learning and Generative Models | 3 |
| STAT 456 | Applied Multivariate Analysis | 3 |
| STAT 461 | Financial Statistics | 3 |
| STAT/COMP SCI 471 | Introduction to Computational Statistics | 3 |
| STAT 479 | Special Topics in Statistics | 1-3 |
| STAT/B M I 542 | Introduction to Clinical Trials I | 3 |
| STAT/F&W ECOL/HORT 572 | Statistical Methods for Bioscience II | 4 |
| STAT 575 | Statistical Methods for Spatial Data | 3 |
| STAT/B M I 641 | Statistical Methods for Clinical Trials | 3 |
| STAT/B M I 642 | Statistical Methods for Epidemiology | 3 |
| STAT 679 | Special Topics in Statistics | 1-3 |
| STAT 732 | Large Sample Theory of Statistical Inference | 3 |
| STAT/B M I 741 | Survival Analysis Theory and Methods | 3 |
| STAT 760 | Multivariate Analysis I | 3 |
| STAT 761 | Decision Trees for Multivariate Analysis | 3 |
| STAT/B M I 768 | Statistical Methods for Medical Image Analysis | 3 |
| STAT 771 | Statistical Computing | 3 |
| STAT/ECON/GEN BUS 775 | Introduction to Bayesian Decision and Control I | 3 |
| STAT 801 | Advanced Financial Statistics | 3 |
| STAT/MATH 803 | Experimental Design I | 3 |
| STAT 809 | Non Parametric Statistics | 3 |
| STAT 811 | Sample Survey Theory and Method | 3 |
| STAT 834 | Empirical Processes and Semiparametric Inference | 1-3 |
| STAT 840 | Statistical Model Building and Learning | 3 |
| STAT 841 | Nonparametric Statistics and Machine Learning Methods | 3 |
| STAT 849 | Theory and Application of Regression and Analysis of Variance I | 3 |
| STAT 850 | Theory and Application of Regression and Analysis of Variance II | 3 |
| STAT 860 | Estimation of Functions from Data | 3 |
| STAT/COMP SCI/E C E 861 | Theoretical Foundations of Machine Learning | 3 |
| STAT/B M I 877 | Statistical Methods for Molecular Biology | 3 |
| STAT 992 | Seminar | 1-3 |
| List 2 (at most one course) : | ||
| STAT/MATH 309 | Introduction to Probability and Mathematical Statistics I | 3 |
| STAT 311 | Introduction to Theory and Methods of Mathematical Statistics I | 3 |
| STAT 609 | Mathematical Statistics I | 3 |
| STAT/MATH 709 | Mathematical Statistics | 4 |
| List 3 (at most one course): | ||
| STAT/MATH 310 | Introduction to Probability and Mathematical Statistics II | 3 |
| STAT 312 | Introduction to Theory and Methods of Mathematical Statistics II | 3 |
| STAT 610 | Introduction to Statistical Inference | 4 |
| STAT/MATH 710 | Mathematical Statistics | 4 |
| List 4 (at most one course): | ||
| STAT/MATH 431 | Introduction to the Theory of Probability | 3 |
| STAT/COMP SCI/MATH 475 | Introduction to Combinatorics | 3 |
| STAT/COMP SCI/I SY E/MATH 525 | Linear Optimization | 3 |
| STAT/I SY E/MATH/OTM 632 | Introduction to Stochastic Processes | 3 |
| STAT/COMP SCI/I SY E/MATH 726 | Nonlinear Optimization I | 3 |
| STAT/MATH 733 | Theory of Probability I | 3 |
| STAT/MATH 833 | Topics in the Theory of Probability | 3 |
| OR another course approved by the Ph.D. minor advisor. | ||
The student must achieve a 3.00 GPA in courses used to satisfy the minor requirement.
Faculty:
Cecile Ane, Professor
Joshua Cape, Assistant Professor
Richard Chappell, Professor
Peter Chien, Professor
Yinqiu He, Assistant Professor
Jessi Cisewski-Kehe, Assistant Professor
Deshpande, Sameer, Assistant Professor
Nicolas Garcia Trillos, Assistant Professor
Hyunseung Kang, Assistant Professor
Sunduz Keles, Professor
Bret Larget, Professor
Keith Levin, Assistant Professor
Wei-Yin Loh, Professor
Michael Newton, Professor
Vivak Patel, Assistant Professor
Alejandra Quintos, Assistant Professor
Sebastian Raschka, Assistant Professor
Garvesh Raskutti, Associate Professor
Karl Rohe, Professor
Kris Sankaran, Assistant Professor
Jun Shao, Professor
Miaoyan Wang, Assistant Professor
Yahzen Wang (chair), Professor
Brian Yandell, Professor
Chunming Zhang, Professor
Zhengjun Zhang, Professor
Yiqiao Zhong, Assistant Professor
Jun Zhu, Professor