Introduction to Data Analysis with R for Forensic Scientists (Hardcover)

James Michael Curran

ISBN 10: 1420088262 / ISBN 13: 9781420088267

Published by Taylor & Francis Inc, Bosa Roca, 2010

About this Item

Hardcover. Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed. However, many researchers lack the statistical skills or resources that would allow them to explore their data to its full potential. Introduction to Data Analysis with R for Forensic Sciences minimizes theory and mathematics and focuses on the application and practice of statistics to provide researchers with the dexterity necessary to systematically analyze data discovered from the fruits of their research.Using traditional techniques and employing examples and tutorials with real data collected from experiments, this book presents the following critical information necessary for researchers: A refresher on basic statistics and an introduction to R Considerations and techniques for the visual display of data through graphics An overview of statistical hypothesis tests and the reasoning behind them A comprehensive guide to the use of the linear model, the foundation of most statistics encountered An introduction to extensions to the linear model for commonly encountered scenarios, including logistic and Poisson regression Instruction on how to plan and design experiments in a way that minimizes cost and maximizes the chances of finding differences that may exist Focusing on forensic examples but useful for anyone working in a laboratory, this volume enables researchers to get the most out of their experiments by allowing them to cogently analyze the data they have collected, saving valuable time and effort. An introduction to statistical data analysis techniques with the emphasis on research work in the laboratory. It explains standard data analytical techniques with a relatively low amount of mathematics, and with a high emphasis on practical usage. It demonstrates what can and cannot be done with statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781420088267

Bibliographic Details

• Title: Introduction to Data Analysis with R for Forensic Scientists (Hardcover)
• Publisher: Taylor & Francis Inc, Bosa Roca
• Publication Date: 2010
• Language: English
• ISBN 10: 1420088262
• ISBN 13: 9781420088267
• Binding: Hardcover
• Condition: new

About this title

Synopsis

Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed. However, many researchers lack the statistical skills or resources that would allow them to explore their data to its full potential. Introduction to Data Analysis with R for Forensic Sciences minimizes theory and mathematics and focuses on the application and practice of statistics to provide researchers with the dexterity necessary to systematically analyze data discovered from the fruits of their research.

Using traditional techniques and employing examples and tutorials with real data collected from experiments, this book presents the following critical information necessary for researchers:

• A refresher on basic statistics and an introduction to R
• Considerations and techniques for the visual display of data through graphics
• An overview of statistical hypothesis tests and the reasoning behind them
• A comprehensive guide to the use of the linear model, the foundation of most statistics encountered
• An introduction to extensions to the linear model for commonly encountered scenarios, including logistic and Poisson regression
• Instruction on how to plan and design experiments in a way that minimizes cost and maximizes the chances of finding differences that may exist

Focusing on forensic examples but useful for anyone working in a laboratory, this volume enables researchers to get the most out of their experiments by allowing them to cogently analyze the data they have collected, saving valuable time and effort.

About the Author

James M. Curran is currently an Associate Professor of Statistics in the Department of Statistics at the University of Auckland (Auckland, New Zealand). Dr. Curran is also the co-director of the New Zealand Bioinformatics Institute at the University of Auckland (www.bioinformatics.org.nz).