Modeling with Data: Two-Variable Measurement Data

Some important questions about the world around us involve possible relationships between two variables. For example, we might want to know not only how life expectancy and poverty rates differ from one country to another, but also how national life expectancy correlates with national poverty levels. By allowing us to analyze such questions, the tools and methods of statistics with two-variable measurement data can help us better understand our world, address the challenges of our time, and advocate for change. In M112 Modeling with Two-Variable Measurement Data, you will pose and analyze meaningful statistical questions that yield two-variable measurement data. You will reason with scatter plots, equation models, and quantitative methods to draw conclusions, gain insight into each situation, and generate new questions. As you learn modeling with two-variable measurement data, you will use technology strategically to create and analyze scatter plots to investigate patterns of association between two measured quantities, creating and reasoning with linear equation models where appropriate. The work for this badge builds a foundation for the future study of topics such as statistical inference and data science. Modeling with two-variable measurement data is useful for careers in a variety of fields, like statistics, psychology, biology, and medicine.

XQ has developed a project-based unit aligned to Badge 112 as a part of the XQ Math Algebra 1 course. Find a teacher guide, content overview, and project overview for _Module 6 - Data Dive_ under Learning Principles and Learning Activities, below. You can access the full folder of module materials HERE.