# 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

Statistical Computing

Introduction to the Ethics of Algorithmic Decision Making

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

Visualizing Data

Sampling Theory for Biologists

Experimental Design

Introduction to Stochastic Processes

Introduction to Stochastic Processes II

Service Learning: K-12 Tutoring Experience

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 III

Statistics Seminar

Special Topics in Statistics

Special Topics in Statistics

Special Topics in Statistics

Techniques of Statistical Consulting