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Data Science and Statistics: A Modeling Approach 3,4 Honors (HP) (4673, 4674) - PILOT COURSE - | |||
| Pilot Site: | |
| Pilot course for Crawford, Hoover, Lincoln, Morse, and Point Loma High Schools. Other schools may not offer this course without prior approval from the Interdivisional Curriculum Committee. | |
| Grade Range: | |
| 9–12 | |
| Prerequisites: | |
| Data Science and Statistics: A Modeling Approach 1,2 | |
| Course duration: | |
| Two semesters | |
| Subject area in which graduation credit will be given: | |
| Math: Advanced | |
| UC subject area satisfied: | |
| c - Mathematics | |
| Course Description: | |
| This course is the second in a two-course sequence. This sequence is equivalent to an introductory, non-calculus-based college course in data science and statistics. In this Honors capstone course, students explore and model variation and evaluate models to answer critical questions. Students use the statistical programming language R to produce data analyses and data visualizations, aligning R code with the algebraic notation of the General Linear Model used by professional researchers. Authentic datasets and real-world questions are explored while building coding skills using technology used by real data scientists, preparing students for work in a professional environment. | |
| State Course Code(s): | |
| 9259 - Probability and Statistics (Non-Advanced Placement) | |
| Basic Texts and Teaching Guides: | |
| Son and Stigler, Introduction to Statistics: A Modeling Approach, 2022 Supplemental Resources Fries et.al, Practicing connections: A framework to guide instructional design for developing understanding in complex domains, Educational Psychology Review, 2021 Van Merriënboer et al, Blueprints for complex learning: The 4C/ID-model. Educational technology research and development, 2002 | |