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Data Science: Predictive Analysis using Mumbai Temperature Data


This lesson plan will help you to teach Introductory Predictive Analysis through an Exploratory Data Analysis with  Linear Regression assignment. The lesson plan includes a hands-on computer-based classroom activity to be conducted on a dataset of the annual temperature records of Mumbai – a coastal city in Western India, for the span of 1842 to 2019. This activity includes hands-on Python code, and a set of inquiry-based questions that will enable your students to apply their understanding of scatter plots, trendlines, moving averages, heatmaps, correlation coefficients, linear regression, and regression equations.

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 trendlines, linear regression and correlation
  2. Understand linear regression equations and related terms such as correlation coefficients
  3. Use linear regression analyses to describe the temperature rise from the Twentieth century  to recent times (1900-2019)
  4. Discuss how these changes suggest that the planet is facing a significant increase in temperature in the last 50 years


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