MN4441 Advanced Managerial Data Analysis

In this course, students learn to use data to analyze relationships among multiple variables, learn about relationships among variables in a set of data, draw appropriate conclusions about relationships in the real world, and make predictions about the future. We will illustrate the tools and concepts using real-world data, and emphasize best practices and common pitfalls in the collection and interpretation of data. The course helps students become more critical and proficient consumers of statistics and managers of data-driven projects in defense management contexts.

Prerequisite

This course builds on the fundamental tools for analyzing data introduced in MN3041 including: * terminology such as variable, parameter, model, inference, estimation, prediction, error, bias; * common notation; * basic summary statistics and simple linear regression; * fundamentals of probability; * limitations of statistical inferences including sample selection and measurement error.

Lecture Hours

Lab Hours

Course Learning Outcomes

By the end of this course, students should be able to:

Given a data set and a context, answer managerial questions about relationships among variables and communicate the results using appropriate visualizations and summaries.
Given a data set and a context, build and evaluate multivariate regression models for the purpose of predicting quantitative response variables, and be familiar with applicability and limitations of common forecasting models.
Understand common concepts and terminology in machine learning and artificial intelligence.
Given a managerial question, design a plan to collect informative data, following best practices.
Understand the applicability of data analysis tools to DoN operations and logistics management problems.
Build, run, and interpret the results of a simple Monte Carlo simulation model.
Depending on applications, students may acquire one or more additional data-analysis skills such as predicting categorical response variables, inferring and visualizing network relationships, and analyzing text fields.