Course Catalog
Numbers and Reason
Lectures in Applied Statistics
Introduction to Data Science
Statistical Reasoning
Statistical Concepts and Methods for the Social Sciences
Advanced Placement (AP) Statistics
BASIC STATISTICS WITH APPLICATIONS
Statistical Computing
Elements of Statistical Methods
Design of Experiments
Evaluating Social Science Evidence
Data Science and Statistics for Social Sciences I
Case-Based Social Statistics II
Introduction to Probability and Mathematical Statistics I
Introduction to Probability and Mathematical Statistics II
Introduction to Probability and Mathematical Statistics III
Statistical Methods in Engineering and Science
Quantitative Introductory Statistics for Data Science
Probability I
Probability II
Finite Markov Chains and Monte-Carlo Methods
Introduction to Resampling Inference
Research Design and Statistics for HIHIM
Introduction to Machine Learning
Applied Statistics and Experimental Design
Applied Regression and Analysis of Variance
Introduction to Nonparametric Statistics
Introduction to Analysis of Categorical Data
Multivariate Analysis for the Social Sciences
Introduction to Statistical Machine Learning
Multivariate Statistical Methods
Sampling Theory for Biologists
Experimental Design
Introduction to Stochastic Processes
Introduction to Stochastic Processes II
Service Learning: K-12 Tutoring Experience
Special Topics
Undergraduate Research
Design and Analysis of Experiments
Practical Methods for Data Analysis
Applied Regression
Applied Probability and Statistics
Econometrics I: Introduction to Mathematical Statistics
Statistical Inference
Statistical Inference
Stochastic Modeling of Scientific Data
Stochastic Modeling of Scientific Data
Stochastic Modeling Project
Time Series Analysis
Spectral Analysis of Time Series
Advanced Probability
Advanced Probability
Advanced Probability
Design of Medical Studies
Nonparametric Regression and Classification
Applied Statistics Capstone
Sample Survey Techniques
Wavelets: Data Analysis, Algorithms, and Theory
Theory of Linear Models
Statistical Computing
Statistical Learning: Modeling, Prediction, and Computing
Analysis of Categorical and Count Data
Statistical Learning: Modeling, Prediction, and Computing
Statistical Learning: Modeling, Prediction and Computing
Multivariate Analysis
Bayesian Statistical Methods
Options and Derivatives
Machine Learning for Big Data
Statistical Methods for Portfolios
Statistical Genetics I: Mendelian Traits
Statistical Genetics II: Quantitative Traits
Statistical Genetics III: Design and Analysis
Statistical Methods for Spatial Data
Introduction to Statistics and Probability
Applied Statistics and Experimental Design
Statistical Machine Learning for Data Scientists
Measure Theory
Hierarchical Modeling for the Social Sciences
Special Topics in Applied Statistics
Special Topics in Applied Statistics
Statistical Demography
Bayesian Statistics for the Social Sciences
Causal Modeling
Statistical Analysis of Social Networks
Advanced Regression Methods for Independent Data
Advanced Regression Methods for Dependent Data
Preparation for Research Prelim
Statistical Methods for Survival Data
Special Topics in Advanced Biostatistics
Data Analysis and Reporting
Advanced Theory of Statistical Inference I
Advanced Theory of Statistical Inference II
Advanced Theory of Statistical Inference
Statistics Seminar
Special Topics in Statistics
Special Topics in Statistics
Special Topics in Statistics
Techniques of Statistical Consulting
Statistical Consulting
Independent Study or Research