Matthew Russell - Böcker

To manage our environment sustainably, professionals must understand the quality and quantity of our natural resources. Statistical analysis provides information that supports management decisions and is universally used across scientific disciplines. Statistics in Natural Resources: Applications with R focuses on the application of statistical analyses in the environmental, agricultural, and natural resources disciplines. This is a book well suited for current or aspiring natural resource professionals who are required to analyze data and perform statistical analyses in their daily work. More seasoned professionals who have previously had a course or two in statistics will also find the content familiar. This text can also serve as a bridge between professionals who understand statistics and want to learn how to perform analyses on natural resources data in R.The primary goal of this book is to learn and apply common statistical methods used in natural resources by using the R programming language. If you dedicate considerable time to this book, you will:Develop analytical and visualization skills for investigating the behavior of agricultural and natural resources data.Become competent in importing, analyzing, and visualizing complex data sets in the R environment.Recode, combine, and restructure data sets for statistical analysis and visualization.Appreciate probability concepts as they apply to environmental problems.Understand common distributions used in statistical applications and inference.Summarize data effectively and efficiently for reporting purposes.Learn the tasks required to perform a variety of statistical hypothesis tests and interpret their results.Understand which modeling frameworks are appropriate for your data and how to interpret predictions.Includes over 130 exercises in R, with solutions available on the book’s website.

To manage our environment sustainably, professionals must understand the quality and quantity of our natural resources. Statistical analysis provides information that supports management decisions and is universally used across scientific disciplines. Statistics in Natural Resources: Applications with R focuses on the application of statistical analyses in the environmental, agricultural, and natural resources disciplines. This is a book well suited for current or aspiring natural resource professionals who are required to analyze data and perform statistical analyses in their daily work. More seasoned professionals who have previously had a course or two in statistics will also find the content familiar. This text can also serve as a bridge between professionals who understand statistics and want to learn how to perform analyses on natural resources data in R.The primary goal of this book is to learn and apply common statistical methods used in natural resources by using the R programming language. If you dedicate considerable time to this book, you will:Develop analytical and visualization skills for investigating the behavior of agricultural and natural resources data.Become competent in importing, analyzing, and visualizing complex data sets in the R environment.Recode, combine, and restructure data sets for statistical analysis and visualization.Appreciate probability concepts as they apply to environmental problems.Understand common distributions used in statistical applications and inference.Summarize data effectively and efficiently for reporting purposes.Learn the tasks required to perform a variety of statistical hypothesis tests and interpret their results.Understand which modeling frameworks are appropriate for your data and how to interpret predictions.Includes over 130 exercises in R, with solutions available on the book’s website.

Far too often in the ?eld of archeology, the wheel of understanding and insight has a narrow focus that fails to recognize critical studies. Crucial information rega- ing pivotal archeological investigations at a variety of sites worldwide is extremely dif?cult, if not impossible, to obtain. The majority of archeological analysis and reporting, at best, has limited publication. The majority of archeological reports are rarely seen and when published are often only in obscure or out-of-print journals – the reports are almost as hard to ?nd as the archeological sites themselves. There is a desperate need to pull seminal archeological writings together into single issue or thematic volumes. It is the int- tion of this series, When the Land Meets the Sea, to address this problem as it relates to archeological work that encompasses both terrestrial and underwater archeology on a single site or on a collection of related sites. For example, despite the fact that we know that bays and waterways structured historic settlement, there is a lack of archeological literature that looks at both the nautical and terrestrial signatures of watersheds in?uence on historic culture.

Far too often in the ?eld of archeology, the wheel of understanding and insight has a narrow focus that fails to recognize critical studies. Crucial information rega- ing pivotal archeological investigations at a variety of sites worldwide is extremely dif?cult, if not impossible, to obtain. The majority of archeological analysis and reporting, at best, has limited publication. The majority of archeological reports are rarely seen and when published are often only in obscure or out-of-print journals – the reports are almost as hard to ?nd as the archeological sites themselves. There is a desperate need to pull seminal archeological writings together into single issue or thematic volumes. It is the int- tion of this series, When the Land Meets the Sea, to address this problem as it relates to archeological work that encompasses both terrestrial and underwater archeology on a single site or on a collection of related sites. For example, despite the fact that we know that bays and waterways structured historic settlement, there is a lack of archeological literature that looks at both the nautical and terrestrial signatures of watersheds in?uence on historic culture.