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Apr 30, 2024
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ECON 2200 - Introduction to Economic Data Analysis Using Python
This course introduces programming and statistics to students from different majors and teaches techniques that apply across many disciplines. No prior programming or statistics experience is necessary. The course introduces students to Python programming language to develop the ability to apply economic analysis and prediction techniques to real-world scenarios through working with real-world data sets. Topics covered include data types, tables, sequences, visualization, causality and experiments, testing hypotheses, estimation, prediction, and inference for regression.
Requisites: (ECON 1030 or ECON 1040) and (Math 1200 or Math 1260 or Math 1350 or Math Placement Level 2)
Credit Hours: 3
Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes: - Students will be able to analyze real-world data sets using Python programming language.
- Students will be able to write loops and selection structures.
- Students will be able to execute basic input/output operations and assignment statements.
- Students will be able to input/output data using text files.
- Students will be able to discuss common programming errors and how to debug a program.
- Students will be able to apply basic strings and string library functions.
- Students will be able to apply economic analysis and prediction techniques to real-world scenarios.
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