Introduction to Data Science (IDS) Curriculum teaches students to reason with, and think critically about, data in all forms. The Common Core State Standards (CCSS) for High School Statistics and Probability relevant to data science are taught along with the data demands of good citizenship in the 21st century. Additionally, IDS provides access to rigorous learning that fuses mathematics with computer science through the use of R/RStudio, an open-source programming language/environment that has long been the standard for academic statisticians and analysts in industry. IDS is a “c”-approved mathematics course in the University of California A-G requirements. IDS directly addresses the CCSS-Math for High School Statistics and Probability and Practice for Modeling.
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Curriculum Overview |
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Unit # | Title | Description |
Unit 1 | Data and Visualizations | Introduces students to fundamental notions of data analysis—such as distribution and multivariate associations and emphasizes creating and interpreting visualizations of real-world processes as captured by data |
Unit 2 | Distributions, Probability, and Simulations | Students use numerical summaries to describe distributions and introduces probability through the lens of computer simulations for informal inference |
Unit 3 | Data Collection Methods: Traditional and Modern | Prepares students to learn about the various ways of collecting data, including Participatory Sensing, and the effect that data collection has on their interpretation of the patterns they discover |
Unit 4 | Predictions and Models | Students learn to make and how to use mathematical and statistical models to predict future observations and how data scientists measure the success of these predictions |
CCSS-Math addressed by IDS | |
Test Drive Our Technology | |
IDS Topic Outline | |
IDS Table of Contents | |
IDS Essential Concepts Outline | |
IDS Participatory Sensing Campaigns Food Habits Time Use Stress-Chill |
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