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Think, Do, and Communicate Environmental Science

Think, Do, and Communicate Environmental Science - Tara Ivanochko

Think, Do, and Communicate Environmental Science


Many students find it daunting to move from studying environmental science, to designing and implementing their own research proposals. This book provides a practical introduction to help develop scientific thinking, aimed at undergraduate and new graduate students in the earth and environmental sciences. Students are guided through the steps of scientific thinking using published scientific literature and real environmental data. The book starts with advice on how to effectively read scientific papers, before outlining how to articulate testable questions and answer them using basic data analysis. The Mauna Loa CO2 dataset is used to demonstrate how to read metadata, prepare data, generate effective graphs and identify dominant cycles on various timescales. Practical, question-driven examples are explored to explain running averages, anomalies, correlations and simple linear models. The final chapter provides a framework for writing persuasive research proposals, making this an essential guide for students embarking on their first research project.
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316.12Lei

316.12Lei

351.25 Lei

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Many students find it daunting to move from studying environmental science, to designing and implementing their own research proposals. This book provides a practical introduction to help develop scientific thinking, aimed at undergraduate and new graduate students in the earth and environmental sciences. Students are guided through the steps of scientific thinking using published scientific literature and real environmental data. The book starts with advice on how to effectively read scientific papers, before outlining how to articulate testable questions and answer them using basic data analysis. The Mauna Loa CO2 dataset is used to demonstrate how to read metadata, prepare data, generate effective graphs and identify dominant cycles on various timescales. Practical, question-driven examples are explored to explain running averages, anomalies, correlations and simple linear models. The final chapter provides a framework for writing persuasive research proposals, making this an essential guide for students embarking on their first research project.
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