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Data Science: Linear Regression with Global Average CO2 Concentrations


This lesson plan will help you to teach Introductory Statistics for Data Science through a Linear Regression assignment. The lesson plan includes a hands-on computer-based classroom activity to be conducted on a dataset of Yearly Global Average CO2 Concentrations in parts per million. This activity includes hands-on Python code, a set of inquiry-based questions that will enable your students to apply their understanding of scatter plots, regression equations, correlation coefficients, and linear regression. 

Thus, the use of this lesson plan allows you to integrate the teaching of a climate science topic with a core topic in Mathematics , Statistics and Data Science..

Learning Outcome

The tools in this lesson plan will enable students to:

  1. Learn about linear regression and correlation
  2. Understand linear regression equations and related terms such as correlation coefficients
  3. Use linear regression analyses to describe how global average CO2 concentrations have changed from 1980-2020 (last datapoint). Discuss reasons for changes in global average CO2 concentrations and their impact on Earth’s climate.


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