Classroom/Laboratory Activity: Linear Regression using Global Temperatures

A classroom/lab activity for Statistics teachers to teach about Linear Regression. This activity is based on a dataset on average global temperature anomalies from 1850 to 2019. 

Students will learn about introductory linear regression techniques and will learn to make scatter plots of the data provided. This tool will allow the student to understand changes in the average global temperatures since the industrial revolution. 

Use this tool to help your students find answers to:

  1. What is linear regression?
  2. Plot the average global temperature anomalies on a scatter plot.
  3. What are confidence intervals? What are the confidence interval slopes for global temperature at 25, 50, 100 and 150 years before 2019?
  4. How have human activities impacted average global temperatures since the Industrial revolution?

About the Tool

Tool Name Global Temperature Anomalies
Discipline Mathematics and Statistics
Topic(s) in Discipline Linear regression, Scatter Plot, Confidence Intervals
Climate Topic Climate Variability Record
Type of Tool Activity
Grade Level High School, Undergraduate
Location Global
Language English
Translation
Developed by IPCC, Thomas J. Pfaff (Ithaca College)
Hosted at Sustainability Math
Link Link
Access Offline
Computer Skills Basic

Differential Calculus using Methane Data

A classroom/laboratory activity for Mathematics teachers to teach about Differential Calculus, specifically, about polynomial differentiation focusing on  Tangent Line Problem and Curve Fitting. This activity contains yearly data of the globally averaged marine surface methane from 1984 to 2019. Methane is a major contributor to greenhouse gas emissions – a potential cause of global warming.

Students will learn the use of scatter plot and curve fitting to derive the polynomial differentiation function. Further this activity will allow students to predict future methane concentrations.

Use this tool to help your students find answers to:

  1. What are polynomial differentiation functions?
  2. Derive a polynomial function using the given methane concentration date.
  3. Calculate future methane concentration using polynomial differentiation.

About the Tool

Tool Name Global Marine Surface CH4
Discipline Mathematics and Statistics
Topic(s) in Discipline Differential Calculus, Polynomial Differentiation, Tangent Line Problem, Scatter Plot, Curve Fitting
Climate Topic Classroom/Laboratory Activity
Type of Tool Video (64 mins)
Grade Level High School, Undergraduate
Location  Global
Language English
Translation
Developed by Thomas J. Pfaff (Ithaca College)
Hosted at Sustainability Math
Link Link
Access Offline
Computer Skills Basic

E-Learning Courses on Climate Change

Series of two E-Learning Courses on Introduction to Climate Change and Climate Science

Following are two online courses in Climate Change and Climate Science by the National Resource Centre (NRC) on Climate Change at the Indian Institute of Science Education and Research (IISER), Pune as part of the Annual Refresher Programme in Teaching (ARPIT), Department of Higher Education, Ministry of Human Resources Development, Government of India.

Teaching Module: Analyzing Climate Science Data through Simple Statistical Techniques

A teaching module that demonstrates the use of linear and quadratic regression to analyze Arctic sea ice extent data and the use of graphs, sample correlations, and multiple regression to analyze atmospheric CO2 level data, solar irradiance data, and average global temperature data.

Classroom/Laboratory Activity: Statistical Methods to Determine Trends in Hurricane Intensity

A classroom/laboratory activity to learn about linear slope, trends, confidence intervals, and Student’s t-distribution by calculating trends and uncertainties using hurricane data records over 40 years.

Classroom/Laboratory Activity: Statistical Methods to Determine Historical Temperature Trends

A classroom/laboratory activity to learn about statistical methods to analyze average annual temperatures of major cities in the world (New York and Sydney) and to determine trends in the data.