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Aug 24, 2024
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STAT 215 - Introduction to Data Science Units: 3 Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Introduction to statistical programming and statistical inference with hands-on analysis of real-world datasets, including economic data, document collections, and social networks.
Prerequisites: Completion of GE area B4. Possible Instructional Methods: Entirely On-ground, or Entirely Online, or Hybrid. Grading: A-F or CR/NC (student choice) Course Typically Offered: Spring ONLY
Student Learning Outcomes - Upon successful completion of this course students will be able to: - Apply basic computational skills in descriptive statistics and data visualization, hypothesis testing, confidence intervals, modeling and error analysis, including the use of large data sets.
- Analyze data using appropriate software, including cloud-based software, and to interpret results covering descriptive statistics and data visualization, hypothesis testing, confidence intervals, modeling and error analysis, including the use of large data sets.
- Communicate results involving descriptive statistics and data visualization, hypothesis testing, confidence intervals, modeling and error analysis using reproducible research best practices.
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