Data Analysis in Natural Sciences: An R-Based Approach

From Field to Figures: Essential Methods for Environmental and Life Sciences

Author

Jimmy Moses

Published

March 27, 2025

Preface

Data Analysis in Natural Sciences: An R-Based Approach

Welcome to Data Analysis in Natural Sciences: An R-Based Approach, a comprehensive guide designed for students, professionals, and researchers across the natural sciences. This book provides practical methods for analyzing and visualizing data using R, with applications spanning forestry, agriculture, ecology, marine biology, environmental science, geology, atmospheric science, hydrology, and more.

About the Author

This book has been developed by Dr. Jimmy Moses (PhD) from the School of Forestry, Faculty of Natural Resources, Papua New Guinea University of Technology. With extensive experience in ecological research and data analysis, Dr. Moses has created this resource to support students and researchers in developing essential analytical skills for natural science disciplines.

Target Audience

This book is designed for:

Undergraduate and postgraduate students in natural science disciplines
Researchers seeking to enhance their data analysis capabilities
Technicians working in laboratories and field settings
Professionals in government agencies, NGOs, and private sector
Hobbyists with an interest in analyzing scientific data

The content is relevant to those working in:

Forestry and agroforestry
Agriculture and agronomy
Ecology and conservation
Environmental science
Geography and GIS/remote sensing
Marine biology and fisheries
Botany and plant sciences
Entomology and zoology
Epidemiology and veterinary sciences
Geology and earth sciences
Atmospheric and climate sciences
Hydrology and water resources
Natural resource management
Conservation biology

What You Will Learn

This book will guide you through:

The fundamentals of data analysis with R
Data preparation and management techniques
Exploratory data analysis approaches
Statistical hypothesis testing
Advanced visualization methods
Specialized analyses for environmental and scientific data
Reproducible research practices

How to Use This Book

This book is designed to be both a learning resource and a reference guide. You can read it from start to finish to build your skills progressively, or use specific chapters as needed for particular tasks.

Code examples are provided throughout, and you can run them directly in R or RStudio. Each chapter includes practical examples using real datasets from various natural science disciplines.

Prerequisites

To get the most out of this book, you should have:

Basic computer skills
R and RStudio installed (instructions provided in Chapter 1)
A basic understanding of statistics (helpful but not required)

Acknowledgments

I would like to thank all those who contributed to the development of this book, including colleagues, students, and the open-source community that makes tools like R and RStudio possible.

Let’s begin our journey into the world of data analysis for natural sciences!

--- prefer-html: true --- # Preface {.unnumbered} Welcome to **Data Analysis in Natural Sciences: An R-Based Approach**, a comprehensive guide designed for students, professionals, and researchers across the natural sciences. This book provides practical methods for analyzing and visualizing data using R, with applications spanning forestry, agriculture, ecology, marine biology, environmental science, geology, atmospheric science, hydrology, and more. ## About the Author This book has been developed by **Dr. Jimmy Moses (PhD)** from the School of Forestry, Faculty of Natural Resources, Papua New Guinea University of Technology. With extensive experience in ecological research and data analysis, Dr. Moses has created this resource to support students and researchers in developing essential analytical skills for natural science disciplines. ## Target Audience This book is designed for: - **Undergraduate and postgraduate students** in natural science disciplines - **Researchers** seeking to enhance their data analysis capabilities - **Technicians** working in laboratories and field settings - **Professionals** in government agencies, NGOs, and private sector - **Hobbyists** with an interest in analyzing scientific data The content is relevant to those working in: - Forestry and agroforestry - Agriculture and agronomy - Ecology and conservation - Environmental science - Geography and GIS/remote sensing - Marine biology and fisheries - Botany and plant sciences - Entomology and zoology - Epidemiology and veterinary sciences - Geology and earth sciences - Atmospheric and climate sciences - Hydrology and water resources - Natural resource management - Conservation biology ## What You Will Learn This book will guide you through: - The fundamentals of data analysis with R - Data preparation and management techniques - Exploratory data analysis approaches - Statistical hypothesis testing - Advanced visualization methods - Specialized analyses for environmental and scientific data - Reproducible research practices ## How to Use This Book This book is designed to be both a learning resource and a reference guide. You can read it from start to finish to build your skills progressively, or use specific chapters as needed for particular tasks. Code examples are provided throughout, and you can run them directly in R or RStudio. Each chapter includes practical examples using real datasets from various natural science disciplines. ## Prerequisites To get the most out of this book, you should have: - Basic computer skills - R and RStudio installed (instructions provided in Chapter 1) - A basic understanding of statistics (helpful but not required) ## Acknowledgments {.unnumbered} I would like to thank all those who contributed to the development of this book, including colleagues, students, and the open-source community that makes tools like R and RStudio possible. Let's begin our journey into the world of data analysis for natural sciences!