# Mathematical Statistics Track

This track focuses on the fundamental mathematical theory underlying statistical inference and prediction. It is ideal for students who are interested in pursuing a Ph.D. in Statistics, an advanced degree in a related field requiring strong mathematical preparation, or a career in which a strong background in statistical theory is valuable.

# Major Requirements

Course Topic/Title Course Number Units Prerequisites Theory Requirements Calculus 21-111 and 112, or 21-120 20 or 10 Integration and Approximation 21-122 10 21-112 or 21-120 Multivariate Calc/Analysis 21-256, 21-259, or 21-268 9–10 21-112 or 21-120 Concepts of Mathematics 21-127 10 Linear/Matrix Algebra 21-240, 21-241, or 21-242 10 Probability 36-217, 21-325, 15-359, or 36-225 9 21-112, 21-122, 21-123, 21-256, or 21-259 Statistical Inference 36-226 or 36-326 9 C or higher in 36-217, 36-225, 21-325, or 15-359 Principles of Real Analysis 21-355 9 21-127 and 21-122 Intro to Probability Modeling 36-410 9 36-225, 36-217, 36-325, or 36-625 Two of the following:   Probability and Math Stat I   Intermediate Statistics   Discrete Math   Optimization   Combinatorics   Real Analysis II 36-70036-70521-22821-257 or 21-29221-30121-356 1212 9 9 9 9 21-127 or 15-15121-240/1/2, 21-256, 06-262, or 18-202 21-127 or 15-15121-240, 21-241, 21-242, 21-256, 06-262, or 18-20221-122 and (15-251 or 21-228)(21-259,21-268,or 21-269) and 21-241/2 and 21-355 Data-Analysis Requirements Beginning Data Analysis 36-201 9 Intermediate Data Analysis 36-202, 36-208, or 36-309 9 various Advanced Elective 36-315, 36-303, or 36-46x 9 36-202, 36-208, or 36-309 Special Topics 36-46x 9 various General Elective various 9 various Modern Regression 36-401 9 C or higher in 36-226, 36-326, or 36-625 and pass 21-240 or 21-241 Advanced Methods for Data Analysis 36-402 9 C or higher in 36-401 Computing Requirements Statistical Computing 36-350 or 36-650/750 9 36-202, 36-208, 36-309, 70-208, or equivalent