Relevant Coursework Summary

Political Science

AP Comparative Government

Score: 5

PS 201 American Politics and Government

Grade: A
Analysis of American political institutions and processes, including the constitution, political culture, campaigns and elections, political parties, interest groups, the media, the president, congress, the federal courts, and public policy. Discussion of contemporary and controversial issues in American politics. Emphasis on placing current issues in comparative and historical perspective where relevant.

PS 371: Research Methodology of Political Science

Grade: A+

Research methods in social science and quantitative analysis in political science and public policy including research design, data collection, statistical analysis and computer applications.

PS 342: Politics of China and Japan

Grade: A+
Politics, public policy, and foreign affairs of China and Japan.

PS 308: Supreme Court and Public Policy

Grade: A
The role of the Supreme Court in American politics, with emphasis on the use of litigation as a form of political activity. Readings include relevant court cases as well as descriptions of the Supreme Court in action.

PS 361: Introduction to Political Theory

Grade: A-

Nature and purpose of politics, as treated by such writers as Plato, Aristotle, St. Augustine, Machiavelli, Locke, Rousseau, Mill, Marx, and Nietzsche.

PS 490: Readings and Research in Political Science

Grade: N/A

Extensive readings or research in political science under direct faculty supervision.

Mathematics

MA 341: Applied Differential Equations I

Grade: A-

Differential equations and systems of differential equations. Methods for solving ordinary differential equations including Laplace transforms, phase plane analysis, and numerical methods. Matrix techniques for systems of linear ordinary differential equations.

MA 405: Introduction to Linear Algebra

Grade: A-

This course offers a rigorous treatment of linear algebra, including systems of linear equations, matrices, determinants, abstract vector spaces, bases, linear independence, spanning sets, linear transformations, eigenvalues and eigenvectors, similarity, inner product spaces, orthogonality and orthogonal bases, factorization of matrices.

MA 401: Applied Differential Equations II

Grade: A+

Wave, heat and Laplace equations. Solutions by separation of variables and expansion in Fourier Series or other appropriate orthogonal sets. Sturm-Liouville problems. Introduction to methods for solving some classical partial differential equations.Use of power series as a tool in solving ordinary differential equations.

MA 351: Introduction to Discrete Mathematical Models

Enrolled Currently

Basic concepts of discrete mathematics, including graph theory, Markov chains, game theory, with emphasis on applications; problems and models from areas such as traffic flow, genetics, population growth, economics, and ecosystem analysis.

MA 326: Mathematical Foundations of Data Science

Enrolled for Spring 2025

The course covers foundational mathematical concepts fundamental to data science and data-driven mathematical modeling. The course includes the following topics: basics of machine learning, unconstrained optimization, neural networks and overfitting, parameter estimation and sensitivity analysis for mathematical models, and an introduction to topological data analysis. Programming familiarity (Python) is recommended.

Statistics

ST 371: Introduction to Probability and Distribution Theory

Grade: A

Basic concepts of probability and distribution theory for students in the physical sciences, computer science and engineering. Provides the background necessary to begin study of statistical estimation, inference, regression analysis, and analysis of variance.

ST 372: Introduction to Statistical Inference and Regression

Grade: A+

Statistical inference and regression analysis including theory and applications. Point and interval estimation of population parameters. Hypothesis testing including use of t, chi-square and F. Simple linear regression and correlation. Introduction to multiple regression and one-way analysis of variance.

ST 307: Introduction to Statistical Programming-SAS

Grade: B+

An introduction to using the SAS statistical programming environment. The course will combine lecture and a virtual computing laboratory to teach students how to use the SAS sytem for: basic data input and manipulation; graphical displays of univariate and bivariate data; one- and two-sample analyses of means; simple linear regression; one-way ANOVA.

ST 430: Introduction to Regression Analysis

Enrolled Currently

Regression analysis as a flexible statistical problem solving methodology. Matrix review; variable selection; prediction; multicolinearity; model diagnostics; dummy variables; logistic and non-linear regression. Emphasizes use of computer.

ST 432: Introduction to Survey Sampling

Enrolled Currently

Design principles pertaining to planning and execution of a sample survey. Simple random, stratified random, systematic and one- and two-stage cluster sampling designs. Emphasis on statistical considerations in analysis of sample survey data. Class project on design and execution of an actual sample survey.

ST 431: Introduction to Experimental Design

Enrolled for Spring 2025
Introduction to Experimental Design:
Experimental design as a method for organizing analysis procedures. Completely randomized, randomized block, factorial, nested, latin squares, split-plot and incomplete block designs. Response surface and covariance adjustment procedures. Stresses use of computer.