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Statistical Exploration of Climate Data

By Tamra Carpenter1, Jon Kettenring2, Robert Vanderbei3

1. DIMACS, Rutgers University 2. Research Institute for Scientists Emeriti, Drew University 3. Princeton University

In this module the students will learn some basic concepts in statistical thinking about data, with emphasis on exploratory data analysis.

Listed in Teaching Materials

Version 1.0 - published on 30 Oct 2018 doi:10.25334/Q4GH8W - cite this

Licensed under CC Attribution-NonCommercial-ShareAlike 4.0 International according to these terms

Screenshot from 2018-10-30 02-58-31.png

Description

In this module the students will learn some basic concepts in statistical thinking about data, with emphasis on exploratory data analysis. The module will analyze daily temperature data collected over 55 years at a single location. The analysis explores the question, 4Is there any observable temperature trend over this time period at this location?! The challenge is to see a potentially small change within a data set that has both seasonal variability and high daily variability. Basic plots are done to help the students view data in different ways, introduce methods for removing seasonality, and use averaging to reduce day-to-day variability. This module might be viewed as a 4case study! in data analysis. It will give students a taste of what it-F"s like to do -Y4real world! data analysis. Students will work with a large noisy data set and look at it in different ways to try to answer a specific question.

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