“Teaching IDS has continued to show me that I am a lifelong learner in the content area of math. Observing my students see math in the tangible real life context with everyday activities involving their electronic devices has allowed me to see the kind of connection and engagement that is not frequently seen in the traditional curriculum of mathematics. Overall, teaching this curriculum has been an eye-opening experience with increased student engagement.”
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
Unit2
Distributions, Probability, and Simulations
Students use numerical summaries to describe distributions and introduces probability through the lens of computer simulations for informal inference
Unit3
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 theydiscover
Unit4
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