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:

• Use appropriate graphical techniques and descriptive statistics to summarize and communicate information contained in data.
• Use the laws of probability to calculate the likelihood of certain events and outcomes, including probabilities conditional on other events.
• Be able to identify sources of variability in data and error in inference, how they affect inference, and how sample data can and should be used to make inferences about a larger population.
• Interpret linear relationships, including trends, and understand the limitations of a linear regression analysis; and
• Critically and effectively interpret and evaluate data and statistics in professional and personal contexts.