This unit contains two main ideas: interpreting data using measures of center and spread, and modeling data with an emphasis on linear models. Students make comparisons between graphs, lists, and tables of multiple data sets by describing the shape, center, spread, and extreme values. Linear models are emphasized, but quadratic and exponential models are mentioned. Linear models should be approximated for appropriate data sets and interpreted in context of the data set. Students should develop a conceptual understanding of correlation and causation and recognize that correlation does not imply causation. While regression is not formally discussed in this unit, foundational understandings are developed.
- How do we use evidence to support arguments?
- How do we interpret evidence in order to support arguments?