This is a repository for the datasets and R codes of "Exploring Climate Change Data with R", a book chapter authored by Nuno Guimarães, Kimmo Vehkalahti, Pedro Campos, and Joachim Engel.
Pre-print draft available here Do not post to other websites or circulate without authors' written consent This manuscript is copyrighted (C) to the authors
The final manuscript appears in Chapter 11 in the book: Statistics for empowerment and social engagement: teaching Civic Statistics to develop informed citizens. (Chief Editor: Jim Ridgway). The chapter is available here
Nuno Guimarães, LIAAD-INESCTEC and University of Porto, Portugal Kimmo Vehkalahti, University of Helsinki, Finland Pedro Campos, LIAAD-INESCTEC and University of Porto, Portugal Joachim Engel,Ludwigsburg University of Education,Germany
Climate change is an existential threat facing humanity and the future of our planet. The signs of global warming are everywhere, and they are more complex than just the climbing temperatures. Climate data on a massive scale has been collected by various scientific groups around the globe. Exploring and extracting useful knowledge from large quantities of data requires powerful software. In this chapter we present some possibilities for exploring and visualising climate change data in connection with statistics education using the freely accessible statistical programming language R together with the computing environment RStudio. In addition to the visualisations, we provide annotated references to climate data repositories and extracts of our openly published R scripts for encouraging teachers and students to reproduce and enhance the visualisations.
Keywords: R; Coding; Climate Data; Data Visualisation;Multivariate Data
Proposed citation for this chapter : Guimarães, N., Vehkalahti, K., Campos, P., Engel, J. (2022). Exploring Climate Change Data with R. In: Ridgway, J. (eds) Statistics for Empowerment and Social Engagement. Springer, Cham. https://doi.org/10.1007/978-3-031-20748-8_11
@Inbook{Guimarães2022,
author="Guimar{\~a}es, Nuno
and Vehkalahti, Kimmo
and Campos, Pedro
and Engel, Joachim",
editor="Ridgway, Jim",
title="Exploring Climate Change Data with R",
bookTitle="Statistics for Empowerment and Social Engagement: Teaching Civic Statistics to Develop Informed Citizens",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="267--296",
abstract="Climate change is an existential threat facing humanity and the future of our planet. The signs of global warming are everywhere, and they are more complex than just the climbing temperatures. Climate data on a massive scale has been collected by various scientific groups around the globe. Exploring and extracting useful knowledge from large quantities of data requires powerful software. In this chapter we present some possibilities for exploring and visualising climate change data in connection with statistics education using the freely accessible statistical programming language R together with the computing environment RStudio. In addition to the visualisations, we provide annotated references to climate data repositories and extracts of our openly published R scripts for encouraging teachers and students to reproduce and enhance the visualisations.",
isbn="978-3-031-20748-8",
doi="10.1007/978-3-031-20748-8_11",
url="https://doi.org/10.1007/978-3-031-20748-8_11"
}
Effective citizen engagement with social issues requires active participation and a broad understanding of data and statistics about societal issues. However, many statistics curricula are not designed to teach relevant skills nor to improve learners' statistical literacy. This book offers practical approaches to working in a new field of knowledge - Civic Statistics - which sets out to engage with, and overcome well documented and long-standing problems in teaching quantitative skills. The book includes 23 peer-reviewed chapters, written in coordination by an international group of experts from ten countries. The book aims to support and enhance the work of teachers and lecturers working both at the high school and tertiary (university) levels. It is designed to promote and improve the critical understanding of quantitative evidence relevant to burning social issues – such as epidemics, climate change, poverty, migration, natural disasters, inequality, employment, and racism. Evidence about social issues is provided to the public via print and digital media, official statistics offices, and other information channels, and a great deal of data is accessible both as aggregated summaries and as individual records. Chapters illustrate the approaches needed to teach and promote the knowledge, skills, dispositions, and enabling processes associated with critical understanding of Civic Statistics presented in many forms. These include statistical analysis of authentic multivariate data, use of dynamic data visualisations, and deconstructing texts about the social and economic well-being of societies and communities. Chapters discuss ideas regarding the development of curricula and educational resources, use of emerging technologies and visualizations, preparation of teachers and teaching approaches and sources for relevant datasets and rich texts about Civic Statistics, and ideas regarding future research, assessment, collaborations between different stakeholders, and other systemic issues.
Nuno Guimarães: nuno.r.guimaraes at inesctec.pt