Module: Exploratory Time Series Analysis in R

A workshop covering modeling and analysis of climate-change time-series data using R.

Learning Outcomes

Learn Exploratory Data Analysis of a Time Series in R

Workshop Description

This workshop will cover the fundamentals of descriptive models and methods for exploring characteristics of time series. Attendees will learn how to decompose and analyze a time series’ secular trend, seasonal, cyclical, and irregular variability components; create descriptive additive/multiplicative models of time series; and explore characteristics of stationarity, autocorrelation, and cross-correlation with other time series. The workshop aims to investigate the practical application of Exploratory Data Analysis (EDA) using NOAA/GML climate change data, including factors like Annual Surface Temperature Change, CO2 concentration, and the frequency of climate-related disasters. The session will involve hands-on EDA using the R programming language.

Learning Outcomes

  1. Grasp the process of decomposing time series utilizing climate change data available on the R-Studio server during the workshop.
  2. Comprehend the exploratory techniques applied to time series analysis by breaking down climate change trends and variations to discern underlying causes and contributing factors.
  3. Acquire practical experience using R as a tool for exploratory time series analysis.
  4. Recognize the significance of exploratory data analysis in time series, acknowledging its pivotal role in achieving a more precise understanding of time series data.

Primary Outcomes

Secondary Outcomes



A few things to complete prior to this workshop


An overview of his workshop

Experiential Learning

1. Ice Breaker: Climate Fresk

Complete the Climate Fresk Challenge

Lab & Mini Lecture 1: What is Time Series Data?

Introduction to Time Series Data

Lab & Mini Lecture 2: Stationarity

Testing for Stationarity

Lab & Mini Lecture 3: Modeling & Cross-Correlating

Explore causality through decomposing time series and then cross-correlating data sets.


Help Us Assess This Workshop

Provide feedback to the workshop organizers

Outcome(s) assessed: You understand basic machine learning concepts