In this course, we will explore approaches for structuring, quantifying, and analyzing common business decisions. We will also explore the various uses of data and statistical inference to drive better decision making. This course aims, in part, to improve your analytical skills by gaining insight into risk and uncertainty. Tools and techniques to support this objective will include decision trees, simulation, hypothesis testing, and regression.

Engage with and train in the use of key concepts in machine learning and math: OLS estimator for regression; logistic regression & maximum likelihood estimator; multiple linear regression; principal components analysis & multiple correspondence analysis; neural networks; logarithms; probability distributions; integrals; multivariate optimization; matrix notation, eigen-math, and matrix decomposition; infinite power series & Taylor series.

Introduction to regression modeling. Topics will be discussed first in the context of linear regression, and then revisited in the context of logistic regression, ordinal regression, proportional hazards regression, and random forests. Students will be required to fit the models (both MLE and Bayesian) and use the strategies discussed in class.

The threat of international terrorism in the wake of 9/11 prompted costly & controversial US military & stabilization efforts in Afghanistan and Iraq. Initially targeting terrorism, it expanded into regime change. Bush, Obama, & Trump administrations struggled to craft effective strategies, facing setbacks like ISIS & Taliban resurgence. What can we learn from this chapter in America¿s endeavor to counter terrorist and security threats abroad?

Business Analytics is useful to the extent that it impacts decision making in an enterprise. Critical to having impact is a thorough understanding of its strategy. This course develops frameworks and tools to analyze the strategy of an organization and develops the skills to evaluate decisions inside an organization. This course will connect your analytical skills with the ability to influence the enterprise as it executes its strategy.

Data visualizations weave information into insights that add business-relevant value. Visual storytelling creates compelling arguments that inspire people to act. Analyzing data sets, finding insights, and turning insights into persuasive storytelling are critical to persuading audiences. We will explore constructing data visualizations using storytelling, visuals, key language, callouts, BLUFs, and other related data visualization elements.

This course will introduce students to both the process of public policy and the tools of policy analysis. The first part examines the actors, institutions, and procedures involved in the adoption, implementation, and evaluation of public policy. The second part introduces students to the basic concepts and tools of policy analysis including problem definition, specification of alternatives, and solution analysis.

Introduces ways that data and information have historically been constructed in different realms--from medicine to public health to computing--to shed light on the power relationships embedded in some of our present-day and near-future tools, systems, and economic relationships. Will use a historical lens, as well as methods from STS, to give an introduction to how data and power interact in people's lives.

Provides an intro to the research process for the allied healthcare professional. The purpose, conduct and eval. of research will be discussed using examples from the health sciences literature. At the conclusion of the course, students will possess the skills to propose and present a basic health sciences research proposal and critically eval. the sources and substance of health related sources and literature. Prereq: PSHM 3010 & PSHM 3050

This course provides an introduction to financial techniques that are essential for leadership dealing with any type of organizational finances. It provides an analytical treatment to valuations based on principles and theories of modern finance. Topics include discounted cash flow; interest rate; capital budgeting; valuation of stocks and bonds; investment decisions under uncertainty; capital asset pricing; option pricing; market efficiency.