MATH Data Science 2

Students will learn to understand, ask questions of, and represent data through project-based units. The units will give students opportunities to be data explorers through active engagement, developing their understanding of data analysis, sampling, correlation/causation, bias and uncertainty, modeling with data, making and evaluating data-based arguments, and the importance of data in society. DATA SCIENCE 2 will include: Linear regression and bivariate data
● Using probability to analyze the fit of a regression
● Make connections between the trend and the context to make predictions
● Spurious correlations, confounding and mediating variables and data ethics
● Evaluating claims: spurious correlation vs causality
● Pros and cons of different ways of data collecting
● Collecting categorical data
● Two-way tables
● Foundations in Linear Algebra: Working in higher dimensional spaces
● Introduction to clustering
● Probability

Credit: 0.5

Length: (1) Trimester

Grade Level: 

Cum Laude Points: 0