Statistics and data analysis are crucial in understanding climate science. When teaching mathematics to high school students with a focus on climate science, it is important to emphasize these topics. Students should learn statistical concepts and methods to effectively analyze climate data. They need to understand data collection, graphical representation, and measures of central tendency to summarize climate variables. Exploring measures of dispersion helps students understand data variability, while correlation and regression analysis help identify relationships and predict trends based on historical data. Interpreting statistical results and drawing meaningful conclusions is another important skill to develop. Concepts such as statistical significance, confidence intervals, and hypothesis testing help students assess the reliability of their findings. Understanding uncertainty and estimating error margins are also essential aspects. By focusing on statistics and data analysis within the context of climate science, students gain the necessary tools to analyze climate data critically, identify trends, and make informed interpretations. These skills are vital for decision-making and addressing the challenges of climate change.

Authors:
Luis Gimeno-Sotelo, University of Vigo, Spain
Maria Joao Valente da Silva Couto, University of Vigo, Spain
Rogert Sorí Gómez, University of Vigo, Spain
Milica Stojanovic, University of Vigo, Spain
Marta Vázquez, University of Vigo, Spain

About the Presenter(s)
Mr Luis Gimeno-Sotelo is a University Doctoral Student at University of Vigo in Spain

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