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Dec 30, 2024
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CAS 5710 - Introduction to Data Analysis
This course introduces students to a comprehensive array of basic descriptive and inferential statistics. Emphasis is placed on inference through a variety of methods including probabilistic approaches, Bayesian analysis, and resampling methods (bootstrapping and jackknifing). Statistical software and an open-source computer programming language are used to reinforce theoretical principles. A strong emphasis is placed upon data visualization and technical graphics for communication of results.
Requisites:
Credit Hours: 3
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:
- Students will be able to match statistical techniques to a variety of substantive problems
- Students will be able to discuss challenges of inference, sampling, and methods of validation
- Students will be able to apply statistical testing to research questions, draw conclusions, and communicate results
- Students will be able to show relationships between quantitative findings, evaluation, and decision-making
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