Introduction to Data Science for Business and Economics
BUSN 5000
3 hours
Introduction to Data Science for Business and Economics
Analytical Thinking
Critical Thinking
Course Description
Harnessing data for decision-making begins with acquiring the raw information and ends with communicating the results of analysis. This course covers the data science skills necessary at every stage of the value chain, including data transformation; descriptive, explanatory and predictive analyses; and professional communication.
Athena Title
Intro to Data Science for Busn
Equivalent Courses
Not open to students with credit in BUSN 5000E
Prerequisite
BUSN 3000 or BUSN 3000E or BUSN 3000H
Grading System
A - F (Traditional)
Student Learning Outcomes
Students will acquire and prepare data for analysis.
Students will design reproducible data analyses.
Students will map business problems and policy questions to hypotheses about relationships in data.
Students will describe data and perform basic descriptive analysis.
Students will implement and interpret basic causal-inference research designs.
Students will implement and interpret basic machine-learning algorithms.
Students will communicate the results from descriptive, causal and predictive analyses.
Topical Outline
Data fundamentals and beginning to learn
Models for exploration
Making inferences
Measurement error, sample selection, and confounding
Bayesian approach to learning from data
Regression fundamentals
Potential outcomes and causal inference
Regression discontinuity
Difference in differences
Introduction to machine learning
Institutional Competencies
Analytical Thinking
The ability to reason, interpret, analyze, and solve problems from a wide array of authentic contexts.
Critical Thinking
The ability to pursue and comprehensively evaluate information before accepting or establishing a conclusion, decision, or action.
