While some qualitative methods texts touch upon online communities as a potential data source, show how to conduct interviews and focus groups online, or select recording devices and analysis software, no book to date has guided readers in the creation of a comprehensive digital workflow for their research. By working through each chapter in this book, readers will be able to generate a unique digital workflow for designing and implementing their research.
A main focus of this book is research questions and the decision-making processes at every step of research. It lays out the factors involved in each part of the research process, from deciding how to limit the scope of a literature review to how to ensure ethical research to deciding which methods to use in a research project. Readers are encouraged to think deeply about each step of the process, providing their own insights throughout, while the book offers a framework for research decisions, rather than a cookie-cutter approach. By developing their knowledge and creating confidence in their own decision-making skills, readers will develop the skills to create a research question, perform a literature review, identify the appropriate method, conduct research, analyze the data and write up an interpretation, all core parts of the research process.
Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business's customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available. Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with R provides readers with a straightforward and applied guide to this new and evolving field.
Introduction to Intelligence: Institutions, Operations, and Analysis offers a strategic, international, and comparative approach to covering intelligence organizations and domestic security issues. Written by multiple authors, each chapter draws on the author's professional and scholarly expertise in the subject matter. As a core text for an introductory survey course in intelligence, this text provides readers with a comprehensive introduction to intelligence, including institutions and processes, collection, communications, and common analytic methods.
This volume of The ANNALS examines the contributions and limitations of scientific research on legacies of racial violence and suggests implications for policy, practice, and other forms of intervention aimed at redress.
Updated with an exciting new chapter on political crime that highlights the debated connections between crime and politics, the Third Edition of White-Collar Crime provides students with a comprehensive introduction to the most important topics within white-collar crime.
Scholars increasingly agree that histories of racial violence relate to contemporary patterns of conflict and inequality, and growing interest exists among civic leaders in reckoning with these legacies today. This volume of The ANNALS examines the contributions and limitations of scientific research on legacies of racial violence and suggests implications for policy, practice, and other forms of intervention aimed at redress.
By exploring qualitative research through a unique analytic lens, then cumulatively elaborating on methods in each successive chapter, this innovative work cultivates a skill set and literacy base that prepares readers to work strategically with empirical materials in their own fieldwork. Renowned authors Johnny Saldana and Matt Omasta combine clear, accessible writing and analytic insight to show that analysis, in its broadest sense, is a process undertaken throughout the entire research experience.
