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 opensource 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 AG requirements. As a statistics course, successful completion of IDS validates Algebra II in California. IDS directly addresses the CCSSMath for High School Statistics and Probability and Practice for Modeling.
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Curriculum Overview 


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 realworld 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 
IDS Brochure 

CCSSMath 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 StressChill 