Here is a step-by-step guide to using this lesson plan in the classroom/laboratory. We have suggested these steps as a possible plan of action. You may customize the lesson plan according to your preferences and requirements.

1.Topic introduction and discussion

Teaching Module(25 min)

Use the teaching module, ‘Introduction-Linear Regression and Correlation’ by OpenStax^TM, Rice University (for High School level) or ‘Chapter-3: Linear Regression’ provided by Ramesh Sridharan, Massachusetts Institute of Technology (for Undergraduate level), to introduce these topics of basic statistics.

 Navigate to the sub-sections within the module to the basics of scatter plots, correlation coefficients, regression equations, and linear regression.

Use the in-built practice exercises and quizzes to evaluate your students’ understanding of the topics.

For High School

For Undergraduate

2. Develop the topic further

Video micro-lecture(~7 min)

Use the video micro-lecture, ‘Confidence interval for the slope of a regression line’ by Khan Academy to explain this inference about a slope.

Navigate to the next subsection and direct your students to solve practice problems on the confidence interval of slope of a regression line to enable better understanding of the topic.

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3.Extend understanding

Classroom/ Laboratory activity(20 min)

1.  Use the classroom activity, ‘Global Temperature Anomalies’ from Sustainability Math by Thomas J. Pfaff, Professor of Mathematics, Ithaca College, USA, to enable your students to apply their understanding of linear regression and confidence intervals of slopes of regression lines by using a dataset developed by Climatic Research Unit (University of East Anglia) in conjunction with the Hadley Centre (UK Met Office).
2.  This classroom activity includes a dataset of Global Temperature Anomalies observed from 1850 to 2017. These observations are taken as deviations from the Global Average Mean temperature for the period 1961-1990.
3. This data is provided in an Excel spreadsheet that you may use in your classroom to explain the mathematical functions and methods.
4.  Direct your students to download the Excel file (with dataset) and proceed with the classroom activity.
5.  Encourage your students to answer topical questions by applying their understanding of scatter plots, correlation coefficients, regression equations, linear regression, and confidence intervals of slopes of regression lines.
6.  Use the regression analyses performed to initiate a discussion on the increase in average global temperatures from pre-industrial time (1850) to the last data point (2017) due to anthropogenically forced Global Warming (links to explanatory notes given within the tool)

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4. Discuss further

Visualization (5 min)

Use the interactive visualization of the same dataset, ‘Average temperature anomaly, Global’ by Our World in Data, to encourage discussion amongst your students about the changes in the average global temperatures from the years 1850-2017.

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5. Questions/Assignments

Use the tools and the concepts learned so far to discuss and determine answers to the following questions:

• Use an example to describe linear regression analysis.
• Determine the difference in the confidence intervals for the slopes for two 30-year period datasets- 1850-1880 (beginning of industrial age) and 1987-2017 (last datapoint). What does the result suggest?
• Use linear regression analyses to describe how global temperatures have changed from 1850 (pre-industrial)- 2017 (last datapoint).
• Discuss reasons for global warming and its impact on Earth’s climate.

Use this lesson plan to help your students find answers to:

1. Use an example to describe linear regression analysis.
2. Determine the difference in the confidence intervals for the slopes for two 30-year period datasets- 1850-1880 (beginning of industrial age) and 1987-2017 (last datapoint). What does the result suggest?
3. Use linear regression analyses to describe how global temperatures have changed from 1850 (pre-industrial)- 2017 (last datapoint).
4. Discuss reasons for global warming and its impact on Earth’s climate.