MN3041 Managerial Data Analysis

This course focuses on the descriptive and inferential statistical concepts and practical analytical skills useful for conducting basic managerial and policy analysis. Topics include descriptive statistics for quantitative and qualitative data, basic probability concepts and distributions, sampling theory and study design, and estimation and prediction using linear models. Prerequisites: College algebra and knowledge of Excel.

Lecture Hours

4

Lab Hours

0

Course Learning Outcomes

At the end of the course, students should be able to:

• Apply the laws of probability to calculate the likelihood of events and outcomes, including those from common probability distributions.
• Interpret data tables, visualizations, and summary statistics to extract meaningful insights.
• Distinguish between population parameters and sample statistics, understand factors affecting sampling error, and estimate its impact.
• Identify and assess sources of variability and error (e.g., measurement error, sample selection bias) and their influence on inference.
• Interpret linear relationships and trends, recognizing the limitations of linear regression analysis.
• Critically evaluate and communicate statistical findings in professional and managerial contexts.