As a high school or undergraduate Mathematics teacher, you can use this set of computer-based tools to help you in teaching introductory statistics and specifically linear regression.
This lesson plan will allow you to teach introductory statistics through a linear regression assignment. The lesson plan includes a hands-on computer-based classroom activity to be conducted on a dataset of Global Temperature Anomalies (1850-2017). This activity includes a set of inquiry-based questions that will enable your students to apply their understanding of scatter plots, regression equations, correlation coefficients, linear regression, and confidence intervals for slopes.
Thus, the use of this lesson plan allows you to integrate the teaching of a climate science topic with a core topic in Mathematics.
Questions
Use this lesson plan to help your students find answers to:
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.
About Lesson Plan
Grade Level
High school, Undergraduate
Discipline
Mathematics
Topic(s) in Discipline
Scatter Plots, Correlation Coefficients, Regression Equations, Linear Regression, Confidence Intervals for Slopes
Climate Topic
Climate and the Cryosphere
Climate Variability Record
Location
Global
Language(s)
English
Access
Online, Offline
Approximate Time Required
50-60 min
Contents
Teaching Module
(25 min)
A teaching module to explain the basics of scatter plots, correlation coefficients, regression equations, and linear regression
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
1. Use the teaching module, ‘Introduction-Linear Regression and Correlation’ by OpenStaxTM, 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.
2. Navigate to the sub-sections within the module to the basics of scatter plots, correlation coefficients, regression equations, and linear regression.
3. Use the in-built practice exercises and quizzes to evaluate your students’ understanding of the topics.
2. 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.
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).
1. 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.
2. Discuss how these changes suggest that the planet is warming and therefore, could be impacting Earth’s climate.
Suggested questions/assignments for learning evaluation :
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.
The tools in this lesson plan will enable students to:
learn about linear regression and correlation
understand linear regression equations and related terms such as correlation coefficients
use linear regression analyses and confidence intervals of slopes of regression lines to describe global temperature anomalies from pre-industrial to recent times (1850-2017)
discuss how these changes suggest that the planet has warmed significantly since the beginning of the industrial age
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1
Teaching Module, “Introduction- Linear Regression and Correlation”
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