Killer Data PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Killer Data PDF full book. Access full book title Killer Data by Enzo Yaksic. Download full books in PDF and EPUB format.
Author: Enzo Yaksic
Publisher: Routledge
ISBN: 1000567265
Category : Social Science
Languages : en
Pages : 111
Get Book Here
Book Description
Killer Data examines the phenomenon of serial murder using data collected from international sources to review offender patterning with a focus on contemporary cases. This type of attention will allow for a broader understanding of modern-day serial murderers and will help to dispel some of the myths that surround offenders. The current serial murder classification scheme incorrectly types serial murderers as supremely intelligent killing machines while discounting their socialization, experiences, and choices. This book exposes serial murderers as run-of-the-mill hometown losers, who brutalize women, and are lucky to escape apprehension. Like other atypical homicide offenders, modern-day serial murderers are propelled forward by a deep sense of entitlement, easy access to firearms, and a nonchalant attitude toward using murder to attain their goals. Readers should come away with a deeper understanding not of the ultra-rare or the "deadliest" serial murderers but of the more common offenders who pose a consistent threat to day-to-day life. The book utilizes the Consolidated Serial Homicide Offender Database, one of the largest and most robust open access databases of multiple murders available, presenting new thinking on areas such as: myths and stereotypes the impact of entertainment on the perception of serial murder inaccurate prevalence estimates spree/serial hybrid offenders the classification of two and three victim serial murderers how serial murderers pursue longevity the characteristics of aspiring serial murderers whether hit men and gang members are serial murderers if and why serial murder is in a state of decline how many serial murderers are responsible for the homicides that sent innocent people to prison luck as a factor of “success” for serial murderers. These findings are illustrated with 200 narrative vignettes of serial murder series that occurred between 2011 and 2021, such as Itzcoatl Ocampo, Charles Severance, Nikko Jenkins, and Pamela Hupp, offenders who may be unfamiliar to many but represent the next iteration of the serial murderer. Correcting decades of flawed assumptions about serial murderers, and written in an accessible and concise style, Killer Data is essential reading for students and scholars of criminal justice and criminology, law enforcement professionals, and the interested general reader.
Author: Enzo Yaksic
Publisher: Routledge
ISBN: 1000567265
Category : Social Science
Languages : en
Pages : 111
Get Book Here
Book Description
Killer Data examines the phenomenon of serial murder using data collected from international sources to review offender patterning with a focus on contemporary cases. This type of attention will allow for a broader understanding of modern-day serial murderers and will help to dispel some of the myths that surround offenders. The current serial murder classification scheme incorrectly types serial murderers as supremely intelligent killing machines while discounting their socialization, experiences, and choices. This book exposes serial murderers as run-of-the-mill hometown losers, who brutalize women, and are lucky to escape apprehension. Like other atypical homicide offenders, modern-day serial murderers are propelled forward by a deep sense of entitlement, easy access to firearms, and a nonchalant attitude toward using murder to attain their goals. Readers should come away with a deeper understanding not of the ultra-rare or the "deadliest" serial murderers but of the more common offenders who pose a consistent threat to day-to-day life. The book utilizes the Consolidated Serial Homicide Offender Database, one of the largest and most robust open access databases of multiple murders available, presenting new thinking on areas such as: myths and stereotypes the impact of entertainment on the perception of serial murder inaccurate prevalence estimates spree/serial hybrid offenders the classification of two and three victim serial murderers how serial murderers pursue longevity the characteristics of aspiring serial murderers whether hit men and gang members are serial murderers if and why serial murder is in a state of decline how many serial murderers are responsible for the homicides that sent innocent people to prison luck as a factor of “success” for serial murderers. These findings are illustrated with 200 narrative vignettes of serial murder series that occurred between 2011 and 2021, such as Itzcoatl Ocampo, Charles Severance, Nikko Jenkins, and Pamela Hupp, offenders who may be unfamiliar to many but represent the next iteration of the serial murderer. Correcting decades of flawed assumptions about serial murderers, and written in an accessible and concise style, Killer Data is essential reading for students and scholars of criminal justice and criminology, law enforcement professionals, and the interested general reader.
Author:
Publisher:
ISBN:
Category : Marine mammals
Languages : en
Pages : 214
Get Book Here
Book Description
Author: Jeffrey S. Simonoff
Publisher: Springer Science & Business Media
ISBN: 0387217274
Category : Social Science
Languages : en
Pages : 508
Get Book Here
Book Description
Categorical data arise often in many fields, including biometrics, economics, management, manufacturing, marketing, psychology, and sociology. This book provides an introduction to the analysis of such data. The coverage is broad, using the loglinear Poisson regression model and logistic binomial regression models as the primary engines for methodology. Topics covered include count regression models, such as Poisson, negative binomial, zero-inflated, and zero-truncated models; loglinear models for two-dimensional and multidimensional contingency tables, including for square tables and tables with ordered categories; and regression models for two-category (binary) and multiple-category target variables, such as logistic and proportional odds models. All methods are illustrated with analyses of real data examples, many from recent subject area journal articles. These analyses are highlighted in the text, and are more detailed than is typical, providing discussion of the context and background of the problem, model checking, and scientific implications. More than 200 exercises are provided, many also based on recent subject area literature. Data sets and computer code are available at a web site devoted to the text. Adopters of this book may request a solutions manual from:
[email protected]. From the reviews: "Jeff Simonoff's book is at the top of the heap of categorical data analysis textbooks...The examples are superb. Student reactions in a class I taught from this text were uniformly positive, particularly because of the examples and exercises. Additional materials related to the book, particularly code for S-Plus, SAS, and R, useful for analysis of examples, can be found at the author's Web site at New York University. I liked this book for this reason, and recommend it to you for pedagogical purposes." (Stanley Wasserman, The American Statistician, August 2006, Vol. 60, No. 3) "The book has various noteworthy features. The examples used are from a variety of topics, including medicine, economics, sports, mining, weather, as well as social aspects like needle-exchange programs. The examples motivate the theory and also illustrate nuances of data analytical procedures. The book also incorporates several newer methods for analyzing categorical data, including zero-inflated Poisson models, robust analysis of binomial and poisson models, sandwich estimators, multinomial smoothing, ordinal agreement tables...this is definitely a good reference book for any researcher working with categorical data." Technometrics, May 2004 "This guide provides a practical approach to the appropriate analysis of categorical data and would be a suitable purchase for individuals with varying levels of statistical understanding." Paediatric and Perinatal Epidemiology, 2004, 18 "This book gives a fresh approach to the topic of categorical data analysis. The presentation of the statistical methods exploits the connection to regression modeling with a focus on practical features rather than formal theory...There is much to learn from this book. Aside from the ordinary materials such as association diagrams, Mantel-Haenszel estimators, or overdispersion, the reader will also find some less-often presented but interesting and stimulating topics...[T]his is an excellent book, giving an up-to-date introduction to the wide field of analyzing categorical data." Biometrics, September 2004 "...It is of great help to data analysts, practitioners and researchers who deal with categorical data and need to get a necessary insight into the methods of analysis as well as practical guidelines for solving problems." International Journal of General Systems, August 2004 "The author has succeeded in writing a useful and readable textbook combining most of general theory and practice of count data." Kwantitatieve Methoden "The book especially stresses how to analyze and interpret data...In fact, the highly detailed multi-page descriptions of analysis and interpretation make the book stand out." Mathematical Geology, February 2005 "Overall, this is a competent and detailed text that I would recommend to anyone dealing with the analysis of categorical data." Journal of the Royal Statistical Society "This important work allows for clear analogies between the well-known linear models for Gaussian data and categorical data problems. ... Jeffrey Simonoff’s Analyzing Categorical Data provides an introduction to many of the important ideas and methods for understanding counted data and tables of counts. ... Some readers will find Simonoff’s style very much to their liking due to reliance on extended real data examples to illuminate ideas. ... I think the extensive examples will appeal to most students." (Sanford Weisberg, SIAM Review, Vol. 47 (4), 2005) "It is clear that the focus of Simonoff’s book is different from other books on categorical data analysis. ... As an introductory textbook, the book is comprehensive enough since all basic topics in categorical data analysis are discussed. ... I think Simonoff’s book is a valuable addition to the literature because it discusses important models for counts ... ." (Jeroen K. Vermunt, Statistics in Medicine, Vol. 24, 2005) "The author based this book on his notes for a class with a very diverse pool of students. The material is presented in such a way that a very heterogeneous group of students could grasp it. All methods are illustrated with analyses of real data examples. The author provides a detailed discussion of the context and background of the problem. ... The book is very interesting and can be warmly recommended to people working with categorical data." (EMS - European Mathematical Society Newsletter, December, 2004) "Categorical data arise often in many fields ... . This book provides an introduction to the analysis of such data. ... All methods are illustrated with analyses of real data examples, many from recent subject-area journal articles. These analyses are highlighted in the text and are more detailed than is typical ... . More than 200 exercises are provided, including many based on recent subject-area literature. Data sets and computer code are available at a Web site devoted to this text." (T. Postelnicu, Zentralblatt MATH, Vol. 1028, 2003) "This book grew out of notes prepared by the author for classes in categorical data analysis. The presentation is fresh and compelling to read. Regression ideas are used to motivate the modelling presented. The book focuses on applying methods to real problems; many of these will be novel to readers of statistics texts ... . All chapters end with a section providing references to books or articles for the inquiring reader." (C.M. O’Brien, Short Book Reviews, Vol. 23 (3), 2003)
Author: Caroline Florence
Publisher: Kogan Page Publishers
ISBN: 1398615048
Category : Business & Economics
Languages : en
Pages : 297
Get Book Here
Book Description
Marketers are storytellers, they write content, marketing strategies and devise internal communications, but unless these stories are evidence-based, they won't be believable or truly persuasive. Understanding how to use data to build and tell stories is an increasingly important part of the modern-day marketers' toolkit. Stories centered on robust evidence and credible data can withstand challenges, provide meaning, offer insight and engage audiences. This book is designed to plug the data storytelling skills gap and enable marketing professionals to cut through the data overload, join the data dots and create engaging narratives and content. Regardless of whether you're a data expert, data anxious or a data sceptic, this book will give you the tools to help you to communicate more effectively with your customers and your stakeholders. Written by expert trainer Caroline Florence, this book outlines how to build robust and compelling data stories. Drawing on her client work with companies such as Toyota, Lactalis, News UK, Mars Petcare and AXA, plus contributions from experts across data, insights, marketing and customer experience, this book provides a practical roadmap to increase your influence with data storytelling.
Author: David Chrisinger
Publisher: JHU Press
ISBN: 1421445840
Category : Computers
Languages : en
Pages : 151
Get Book Here
Book Description
"The value and prominence of data has never been clearer. From the way we make policies at the highest levels, all the way down to our daily business practices, we try to be informed by data. The ability to not only analyze data but also to present it clearly and compellingly has become an important part of many people's work. In clear, well-organized chapters, Chrisinger and Brodsky introduce key concepts for communicating data and its usefulness. Across the fields of public health, health policy, and public policy more generally, but also in many other places, policymakers, advocates, and researchers will benefit from the big-picture overview and practical details presented by the authors"--
Author: Roy Hoffman
Publisher: Springer Science & Business Media
ISBN: 1461560314
Category : Computers
Languages : en
Pages : 424
Get Book Here
Book Description
Data compression is now indispensable to products and services of many industries including computers, communications, healthcare, publishing and entertainment. This invaluable resource introduces this area to information system managers and others who need to understand how it is changing the world of digital systems. For those who know the technology well, it reveals what happens when data compression is used in real-world applications and provides guidance for future technology development.
Author:
Publisher:
ISBN:
Category : Health surveys
Languages : en
Pages : 110
Get Book Here
Book Description
Author: Hamido Fujita
Publisher: Springer
ISBN: 3319420070
Category : Computers
Languages : en
Pages : 1019
Get Book Here
Book Description
This book constitutes the refereed conference proceedings of the 29th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, held in Morioka, Japan, in August 2-4, 2016. The 80 revised full papers presented were carefully reviewed and selected from 168 submissions. They are organized in topical sections: data science; knowledge base systems; natural language processing and sentiment analysis; semantic Web and social networks; computer vision; medical diagnosis system and bio-informatics; applied neural networks; innovations in intelligent systems and applications; decision support systems; adaptive control; soft computing and multi-agent systems; evolutionary algorithms and heuristic search; system integration for real-life applications.
Author: Wendy H. Wong
Publisher: MIT Press
ISBN: 0262048574
Category : Political Science
Languages : en
Pages : 282
Get Book Here
Book Description
A rallying call for extending human rights beyond our physical selves—and why we need to reboot rights in our data-intensive world. Winner of the 2024 Balsillie Prize for Public Policy Shortlisted, 2024 Lionel Gelber Prize Our data-intensive world is here to stay, but does that come at the cost of our humanity in terms of autonomy, community, dignity, and equality? In We, the Data, Wendy H. Wong argues that we cannot allow that to happen. Exploring the pervasiveness of data collection and tracking, Wong reminds us that we are all stakeholders in this digital world, who are currently being left out of the most pressing conversations around technology, ethics, and policy. This book clarifies the nature of datafication and calls for an extension of human rights to recognize how data complicate what it means to safeguard and encourage human potential. As we go about our lives, we are co-creating data through what we do. We must embrace that these data are a part of who we are, Wong explains, even as current policies do not yet reflect the extent to which human experiences have changed. This means we are more than mere “subjects” or “sources” of data “by-products” that can be harvested and used by technology companies and governments. By exploring data rights, facial recognition technology, our posthumous rights, and our need for a right to data literacy, Wong has crafted a compelling case for engaging as stakeholders to hold data collectors accountable. Just as the Universal Declaration of Human Rights laid the global groundwork for human rights, We, the Data gives us a foundation upon which we claim human rights in the age of data.
Author: Aleksejs Plotnikovs
Publisher: Packt Publishing Ltd
ISBN: 1835466931
Category : Computers
Languages : en
Pages : 270
Get Book Here
Book Description
Leverage your data as a business asset, from readiness to actionable insights, and drive exceptional performance Key Features Learn strategies to create a data-driven culture and align data initiatives with business goals Navigate the ever-evolving business landscape with a modern data platform and unique Data IP Surpass competitors by harnessing the true value of data and fostering data literacy in your organization Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMicrosoft pioneered data innovation and investment ahead of many in the industry, setting a remarkable standard for data maturity. Written by a data leader with over 15 years of experience following Microsoft’s data journey, this book delves into every crucial aspect of this journey, including change management, aligning with business needs, enhancing data value, and cultivating a data-driven culture. This book emphasizes that success in a data-driven enterprise goes beyond relying solely on modern technology and highlights the importance of prioritizing genuine business needs to propel necessary modernizations through change management practices. You’ll see how data-driven innovation does not solely reside within central IT engineering teams but also among the data's business owners who rely on data daily for their operational needs. This guide empower these professionals with clean, easily discoverable, and business-ready data, marking a significant breakthrough in how data is perceived and utilized throughout an enterprise. You’ll also discover advanced techniques to nurture the value of data as unique intellectual property, and differentiate your organization with the power of data. Its storytelling approach and summary of essential insights at the end of each chapter make this book invaluable for business and data leaders to advocate for crucial data investments.What you will learn Develop a data-driven roadmap to achieve significant and quantifiable business goals Discover the ties between data management and change management Explore the data maturity curve with essential technology investments Build, safeguard, and amplify your organization's unique Data Intellectual Property Equip business leaders with trustworthy and high value data for informed decision-making Unleash the value of data management and data governance to uplift your data investments Who this book is for This book is for data leaders, CDOs, CDAOs, data practitioners, data stewards, and enthusiasts, as well as modern business leaders intrigued by the transformative potential of data. While a technical background isn't essential, a basic understanding of data management and quality concepts will be helpful. The book avoids twisted technical, engineering, or data science aspects, making it accessible and insightful for data engineers and data scientists to gain a wider understanding of enterprise data needs and challenges.
