Theoretical Statistics Certificate

About the Certificate

The Certificate in Theoretical Statistics is designed to enhance a student’s understanding of theoretical statistics and probability in preparation for employment in the engineering, information science, and technology sectors. The certificate also prepares students for further graduate study.

The minimum required GPA for the awarding of the certificate is 3.0. Consult an advisor in the Department of Statistics and Data Science for clarification and interpretation of requirements. The certificate consists of 12 graduate level units, plus any necessary prerequisites.

Department Courses Listed by Course Type

Statistics, Biostatistics, and Data Science Courses

Department of Statistics and Data Science

Courses

Biostatistics: Graduate

• •  BSTA 661 - Categorical Data Analysis Units: 2
• •  BSTA 662 - Survival Analysis Units: 2
• •  BSTA 663 - Clinical Trials in the Pharmaceutical and Biomedical Industries Units: 2
• •  BSTA 665 - Survival Data Analysis using SAS Units: 4
• •  BSTA 668 - Longitudinal Data Analysis Units: 2
• •  BSTA 697 - Issues in Biostatistics Units: 1-3

Data Science

• •  DATA 105 - Math for Data Science 1 Units: 5 ; Breadth Area: GE-2
• •  DATA 130 - Data Science Profession Units: 2
• •  DATA 205 - Math for Data Science 2 Units: 3
• •  DATA 312 - Data Analysis with Python Units: 3
• •  DATA 340 - Data Science Ethics Units: 3
• •  DATA 492 - Capstone Project Units: 3

Statistics

• •  STAT 100 - Elements of Statistics and Probability Units: 3 ; Breadth Area: GE-2
• •  STAT 100A - Statistics Principles Units: 1
• •  STAT 101 - Statistics in Everyday Life Units: 3 ; Breadth Area: GE-2
• •  STAT 101A - Everyday Statistics Principles Units: 1
• •  STAT 110 - Elements of Statistics for Business and Economics Units: 3
• •  STAT 125 - Introduction to Statistics in Social Sciences Units: 3 ; Breadth Area: GE-2
• •  STAT 125A - Statistics Principles for Social Sciences Units: 1
• •  STAT 130 - Data Science Profession Units: 2
• •  STAT 206 - Public Health Informatics and Technology Units: 3
• •  STAT 215 - Introduction to Data Science Units: 3
• •  STAT 303 - Statistical Methods in Biology Units: 3
• •  STAT 303A - Biostatistics for Health Science Units: 3
• •  STAT 306 - Public Health Informatics: The Role of Data Units: 3
• •  STAT 310 - Statistical Methods in the Social Sciences Units: 3
• •  STAT 312 - Data Analysis with Python Units: 3
• •  STAT 316 - Statistics and Probability for Science and Engineering Units: 3
• •  STAT 320 - Introduction to Probability Theory I Units: 3
• •  STAT 321 - Probability Through Simulation Units: 3
• •  STAT 330 - Statistical Inference Units: 3
• •  STAT 331 - Introduction to Analysis of Variance Units: 3
• •  STAT 340 - Data Science Ethics Units: 3
• •  STAT 351 - Sampling Procedures for Surveys Units: 3
• •  STAT 398 - Internship Units: 1-3
• •  STAT 406 - Emerging Technologies for Public Health Units: 3
• •  STAT 416 - Public Health Maps and Spatial Analysis for Health Equity Units: 3
• •  STAT 432 - Introduction to Linear Regression and Logistic Regression Units: 3
• •  STAT 450 - Introduction to R for Data Science Units: 3
• •  STAT 451 - Introduction to Data Visualization Units: 3
• •  STAT 452 - Introduction to Statistical Learning Units: 3
• •  STAT 473 - Introduction to Nonparametric Statistics Units: 3
• •  STAT 474 - Introduction to Time Series and Forecasting Units: 3
• •  STAT 475 - Introduction to Stochastic Processes Units: 3
• •  STAT 481 - Bayesian Statistics Units: 3
• •  STAT 490 - Independent Study Units: 1-4
• •  STAT 492 - Capstone Project Units: 3
• •  STAT 495 - Data Analysis with SAS Units: 3
• •  STAT 497 - Issues in Statistics Units: 3
• •  STAT 498 - Internship Units: 1-3

Statistics: Graduate

• •  STAT 605 - Teaching Mathematics at the University Level Units: 1
• •  STAT 620 - Probability and Statistical Theory Units: 4
• •  STAT 630 - Statistical Methods Units: 4
• •  STAT 633A - Generalized Linear Models I Units: 4
• •  STAT 633B - Generalized Linear Models II Units: 4
• •  STAT 640 - Advanced Statistical Theory Units: 4
• •  STAT 640A - Advanced Statistical Theory I Units: 2
• •  STAT 640B - Advanced Statistical Theory II Units: 2
• •  STAT 641 - Bootstrapping Methods Units: 2
• •  STAT 650A - Advanced R for Data Science Units: 2
• •  STAT 650B - Python for Data Science Units: 2
• •  STAT 651 - Data Visualization Units: 2
• •  STAT 652 - Statistical Learning Units: 2
• •  STAT 653 - Statistical Natural Language Processing Units: 2
• •  STAT 654 - Introduction to Applied Deep Learning Units: 2
• •  STAT 660 - Advanced SAS I Units: 2
• •  STAT 661 - Categorical Data Analysis Units: 2
• •  STAT 671 - Advanced JMP Units: 2
• •  STAT 673 - Nonparametric Statistical Methods Units: 2
• •  STAT 674 - Time Series Units: 2
• •  STAT 675 - Advanced Stochastic Processes and Simulation Units: 2
• •  STAT 676 - Advanced Probability Units: 4
• •  STAT 690 - Independent Study Units: 1-4
• •  STAT 692 - Comprehensive Exam Review Units: 2
• •  STAT 694 - Applied Research in Statistics and Biostatistics Units: 1-4
• •  STAT 697 - Issues in Statistics Units: 2-4
• •  STAT 698 - Internship Units: 1-3