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R is fast becoming ubiquitous in the environmental sciences to analyse data. This book introduces environmental modeling and R. It assumes no background in either coding or calculus. It offers real-world examples, fully described programs, and detailed exercises. Readers learn how to analyse large datasets, create beautiful images, thoughtfully utilize the benefits of AI, and use techniques like optimization and sensitivity analysis in their modelling of complex environmental systems. Using examples from a range of environmental topics - including ecology, conservation, and climate science - the book will interest readers from a broad range of environmental and conservation sciences. Most graduate programs in environmental science and sustainability use R because it is both open source and powerful. R is common in government and consulting work, so students that go on to more advanced environmental modelling courses and potentially careers in the environmental field will find a grounding in R very useful.
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R is fast becoming ubiquitous in the environmental sciences to analyse data. This book introduces environmental modeling and R. It assumes no background in either coding or calculus. It offers real-world examples, fully described programs, and detailed exercises. Readers learn how to analyse large datasets, create beautiful images, thoughtfully utilize the benefits of AI, and use techniques like optimization and sensitivity analysis in their modelling of complex environmental systems. Using examples from a range of environmental topics - including ecology, conservation, and climate science - the book will interest readers from a broad range of environmental and conservation sciences. Most graduate programs in environmental science and sustainability use R because it is both open source and powerful. R is common in government and consulting work, so students that go on to more advanced environmental modelling courses and potentially careers in the environmental field will find a grounding in R very useful.