Nov 21, 2024

USC Catalogue 2023-2024

USC Catalogue 2023-2024 [ARCHIVED CATALOGUE]

Statistics (MS)

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The object of this program is to provide academic instruction in statistical theory with a solid mathematical foundation while emphasizing applications to real world problems. Some probability theory is included to provide a rigorous foundation. The program is intended for individuals who are seeking or currently hold positions that involve statistical methodology and practice. A student may orient his or her course of study toward a particular field of application through appropriate selections from the program listings plus elective courses from other disciplines.

Course Requirements

Thirty units of course work are required, including:

Required Courses

MATH 541a Introduction to Mathematical Statistics Units: 3
MATH 541b Introduction to Mathematical Statistics Units: 3
MATH 550 Statistical Consulting and Data Analysis Units: 3

And one from each of options A, B, C:

Plus at least 12 units of courses from the following categories, or additional courses approved by the adviser:

Biological Science

Course selected in consultation with an adviser Units: 4

BISC 543 Seminar in Evolution and Adaptation in Marine Organisms Units: 2

Computer Science

CSCI 544 Applied Natural Language Processing Units: 4
CSCI 561 Foundations of Artificial Intelligence Units: 4
CSCI 567 Machine Learning Units: 4
CSCI 570 Analysis of Algorithms Units: 4
CSCI 585 Database Systems Units: 4
CSCI 670x Advanced Analysis of Algorithms Units: 4
CSCI 677 Advanced Computer Vision Units: 4
CSCI 686 Advanced Big Data Analytics Units: 4

Data Sciences and Operations

DSO 528 Blended Data Business Analytics for Efficient Decisions Units: 3
DSO 530 Applied Modern Statistical Learning Methods Units: 3
DSO 536 Monte Carlo Simulation and Decision Models Units: 1.5
DSO 545 Statistical Computing and Data Visualization Units: 1.5, 3

Economics

ECON 513 Practice of Econometrics Units: 4
ECON 610 Quantitative Analysis in Macroeconomics Units: 4
ECON 612 Econometric Theory Units: 4
ECON 613 Economic and Financial Time Series I Units: 4
ECON 614 Economic and Financial Time Series II Units: 4
ECON 615 Applied Econometrics Units: 4

Electrical and Computer Engineering

EE 510 Linear Algebra for Engineering Units: 4
EE 512 Stochastic Processes for Financial Engineering Units: 4
EE 550 Data Networks: Design and Analysis Units: 4
EE 553 Computational Solution of Optimization Problems Units: 3
EE 559 Machine Learning I: Supervised Methods Units: 4
EE 562 Random Processes in Engineering Units: 4
EE 563 Inference and Estimation: Theory and Algorithms Units: 4
EE 588 Optimization for the Information and Data Sciences Units: 4
EE 592 Computational Methods for Inverse Problems Units: 4
EE 649 Stochastic Network Optimization and Adaptive Learning Units: 4
EE 660 Machine Learning II: Mathematical Foundations and Methods Units: 4

Finance and Business Economics

FBE 535 Applied Finance in Fixed Income Securities Units: 1.5, 3 *
FBE 555 Investment Analysis and Portfolio Management Units: 3 *
FBE 559 Management of Financial Risk Units: 3 *

Prerequisite Note:

*GSBA 548 is a prerequisite that may not be waived.

Industrial and Systems Engineering

ISE 520 Optimization Theory and Algorithms: Numerical Optimization Units: 4
ISE 525 Design of Experiments Units: 4
ISE 530 Optimization Methods for Analytics Units: 4
ISE 538 Markov Models for Performance Analysis Units: 4
ISE 539 Stochastic Elements of Simulation Units: 4
ISE 626 Advanced Topics in Applied Stochastic Models

Data Science Program

DSCI 510 Principles of Programming for Data Science Units: 4
DSCI 552 Machine Learning for Data Science Units: 4
DSCI 560 Data Science Professional Practicum Units: 4

Mathematics

MATH 502b Numerical Analysis Units: 3
MATH 508 Filtering Theory Units: 3
MATH 509 Stochastic Differential Equations Units: 3
MATH 512 Financial Informatics and Simulation (Computer Labs and Practitioner Seminar) Units: 3
MATH 530a Stochastic Calculus and Mathematical Finance Units: 3
MATH 530b Stochastic Calculus and Mathematical Finance Units: 3
MATH 545 Introduction to Time Series Units: 3
MATH 547 Mathematical Foundations of Statistical Learning Theory Units: 3
MATH 605 Topics in Probability Units: 3
MATH 606 Topics in Stochastic Processes Units: 3

Preventive Medicine

PM 510L Principles of Biostatistics Units: 4
PM 511aL Data Analysis Units: 4
PM 511bL Data Analysis Units: 4
PM 511cL Data Analysis Units: 4
PM 513 Experimental Designs Units: 3
PM 522a Introduction to the Theory of Statistics Units: 3
PM 522b Introduction to the Theory of Statistics Units: 3
PM 534 Statistical Genetics Units: 3
PM 544L Multivariate Analysis Units: 3
PM 570 Statistical Methods in Human Genetics Units: 4
PM 571 Applied Logistic Regression Units: 3
PM 603 Structural Equation Modeling Units: 4, 2 years

Psychology

PSYC 501L Classic and Modern Statistical Methods I Units: 4
PSYC 502 Classic and Modern Statistical Methods II Units: 4
PSYC 503L Regression and the General Linear Model Units: 4
PSYC 520 Fundamentals of Psychological Measurement Units: 4
PSYC 575L Multilevel Modeling Units: 4
PSYC 577 Analysis of Covariance Structures Units: 4
PSYC 578 Workshop in Quantitative Methods Units: 4

Public Planning and Development

PPD 557 Modeling and Operations Research Units: 4
PPD 558 Multivariate Statistical Analysis Units: 4

Social Work

SOWK 761L Multiple Regression for Social Work Research Units: 3

Sociology

SOCI 521 Quantitative Methods and Statistics Units: 4

Note:

The following courses may not be used as electives for the degree:

DSO 401 , DSO 510 , EE 503 , FBE 529 , FBE 540 , FBE 543 , MATH 505a and MATH 505b or MATH 507a and MATH 507b (other than the course used to satisfy Requirement A), MATH 525a and MATH 525b , MATH 532 , MATH 574 , PPD 502x , PPD 525 and PPD 570

Additional Requirements

Students may opt for a master’s thesis (and registration in MATH 594a , MATH 594b ) or a written examination covering material from MATH 505a or MATH 507a , and MATH 541a , MATH 541b . The examination will normally be given at the beginning of the fall and spring semester. Students must pass MATH 505a or MATH 507a , and MATH 541a , MATH 541b with a grade of B or higher. If a student receives a grade of B- or lower in any of these courses, the requirement can be waived upon passing the screening exam for the course at the master’s level or higher.