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Predictive Crime Analysis using R

Predictive Crime Analysis using R
Author: Jeffrey Strickland
Publisher: Lulu.com
Total Pages: 345
Release: 2019-02-14
Genre: Law
ISBN: 0359431593

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Predictive Crime Analysis using R is Dr. Strickland's second crime analysis book. In this volume, rather than using data to describe crime history, he uses it to predict crime using pattern created with advanced clustering methods, crime series linkage, and text analysis. Coverage includes prediction of conventional crime and terrorist attacks. The open-source software R is introduced and used in developing crime data, including Geo-spatial data, and constructing predictive models and performing post analysis. Using actual crime data from cities like Atlanta, Dr. Strickland also shows how to simulate additional data from actual data. Simulated data can then be used in cities with insufficient actual data, but with similar demographics and human behavior.


Predictive Policing

Predictive Policing
Author: Walt L. Perry
Publisher: Rand Corporation
Total Pages: 187
Release: 2013-09-23
Genre: Computers
ISBN: 0833081551

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Predictive policing is the use of analytical techniques to identify targets for police intervention with the goal of preventing crime, solving past crimes, or identifying potential offenders and victims. These tools are not a substitute for integrated approaches to policing, nor are they a crystal ball. This guide assesses some of the most promising technical tools and tactical approaches for acting on predictions in an effective way.


Foundations of Crime Analysis

Foundations of Crime Analysis
Author: Jeffery T. Walker
Publisher: Routledge
Total Pages: 264
Release: 2018-02-12
Genre: Social Science
ISBN: 1317507010

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In recent years, the fields of crime analysis and environmental criminology have grown in prominence for their advancements made in understanding crime. This book offers a theoretical and methodological introduction to crime analysis, covering the main techniques used in the analysis of crime and the foundation of crime mapping. Coverage includes discussions of: The development of crime analysis and the profession of the crime analyst, The theoretical roots of crime analysis in environmental criminology, Pertinent statistical methods for crime analysis, Spatio-temporal applications of crime analysis, Crime mapping and the intersection of crime analysis and police work, Future directions for crime analysis. Packed with case studies and including examples of specific problems faced by crime analysts, this book offers the perfect introduction to the analysis and investigation of crime. It is essential reading for students taking courses on crime analysis, crime mapping, crime prevention, and environmental criminology. A companion website offers further resources for students, including flashcards and video and website links. For instructors, it includes chapter-by-chapter PowerPoint slides.


Crime Mapping and Spatial Data Analysis using R

Crime Mapping and Spatial Data Analysis using R
Author: Juan Medina Ariza
Publisher: CRC Press
Total Pages: 451
Release: 2023-04-27
Genre: Mathematics
ISBN: 1000850781

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Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.


Predictive Policing and Artificial Intelligence

Predictive Policing and Artificial Intelligence
Author: John McDaniel
Publisher: Routledge
Total Pages: 452
Release: 2021-02-25
Genre: Computers
ISBN: 0429560389

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This edited text draws together the insights of numerous worldwide eminent academics to evaluate the condition of predictive policing and artificial intelligence (AI) as interlocked policy areas. Predictive and AI technologies are growing in prominence and at an unprecedented rate. Powerful digital crime mapping tools are being used to identify crime hotspots in real-time, as pattern-matching and search algorithms are sorting through huge police databases populated by growing volumes of data in an eff ort to identify people liable to experience (or commit) crime, places likely to host it, and variables associated with its solvability. Facial and vehicle recognition cameras are locating criminals as they move, while police services develop strategies informed by machine learning and other kinds of predictive analytics. Many of these innovations are features of modern policing in the UK, the US and Australia, among other jurisdictions. AI promises to reduce unnecessary labour, speed up various forms of police work, encourage police forces to more efficiently apportion their resources, and enable police officers to prevent crime and protect people from a variety of future harms. However, the promises of predictive and AI technologies and innovations do not always match reality. They often have significant weaknesses, come at a considerable cost and require challenging trade- off s to be made. Focusing on the UK, the US and Australia, this book explores themes of choice architecture, decision- making, human rights, accountability and the rule of law, as well as future uses of AI and predictive technologies in various policing contexts. The text contributes to ongoing debates on the benefits and biases of predictive algorithms, big data sets, machine learning systems, and broader policing strategies and challenges. Written in a clear and direct style, this book will appeal to students and scholars of policing, criminology, crime science, sociology, computer science, cognitive psychology and all those interested in the emergence of AI as a feature of contemporary policing.


Crime Mapping and Spatial Data Analysis using R

Crime Mapping and Spatial Data Analysis using R
Author: Juan Medina Ariza
Publisher: CRC Press
Total Pages: 523
Release: 2023-04-27
Genre: Mathematics
ISBN: 100085079X

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Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.


Data Science Applications using R

Data Science Applications using R
Author: Jeffrey Strickland
Publisher: Lulu.com
Total Pages: 434
Release: 2019-11-13
Genre: Business & Economics
ISBN: 035981042X

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To write a single book about data science, at least as I view the discipline, would result in several volumes. I have come to view Data Science as a multidisciplinary field. People who engage in data science may be statisticians, economists, mathematicians, operations research analysts, and a myriad of other scientific professionals. Most would agree that data scientist have advance degrees in one or more of these disciplines. All practitioners would agree that Data is at center stage. This book is intended to demonstrate the multidisciplinary application of data science, using R-programming with R Studio.


A Beginner’s Guide to Statistics for Criminology and Criminal Justice Using R

A Beginner’s Guide to Statistics for Criminology and Criminal Justice Using R
Author: Alese Wooditch
Publisher: Springer Nature
Total Pages: 342
Release: 2021-06-03
Genre: Social Science
ISBN: 3030506258

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This book provides hands-on guidance for researchers and practitioners in criminal justice and criminology to perform statistical analyses and data visualization in the free and open-source software R. It offers a step-by-step guide for beginners to become familiar with the RStudio platform and tidyverse set of packages. This volume will help users master the fundamentals of the R programming language, providing tutorials in each chapter that lay out research questions and hypotheses centering around a real criminal justice dataset, such as data from the National Survey on Drug Use and Health, National Crime Victimization Survey, Youth Risk Behavior Surveillance System, The Monitoring the Future Study, and The National Youth Survey. Users will also learn how to manipulate common sources of agency data, such as calls-for-service (CFS) data. The end of each chapter includes exercises that reinforce the R tutorial examples, designed to help master the software as well as to provide practice on statistical concepts, data analysis, and interpretation of results. The text can be used as a stand-alone guide to learning R or it can be used as a companion guide to an introductory statistics textbook, such as Basic Statistics in Criminal Justice (2020).


Introduction to Crime Analysis

Introduction to Crime Analysis
Author: Deborah Osborne
Publisher: Psychology Press
Total Pages: 182
Release: 2003
Genre: Law
ISBN: 9780789018687

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This book offers a practical guide and resource for those in law enforcement who analyze crime. The target audience is those new to crime analysis, however many resources are presented that should be useful to more experienced crime analysts as well. Chapter 1 provides an introduction of crime analysis, including the challenges involved in defining crime analysis and the reasons for analyzing crimes. The basic types of crime analysis used in most local law enforcement agencies are described, and the authors point out that most agencies are moving toward tactical and strategic methods of crime analysis. Chapter 2 focuses on the tools of crime analysis. Computer skills are an important component of crime analysis, as demonstrated by the many Internet links provided as resources throughout the book. The importance of knowing the law, the investigative process, and modern policing strategies are also underscored in chapter 2. Linkage analysis, statistical analysis, profiling, and spatial analysis are also addressed in this chapter. Chapter 3 describes the stages of crime analysis: evidence collection, collation, analysis, dissemination, feedback, and evaluation. The Intelligence Cycle of crime analysis is also briefly presented. Chapter 4 turns to a discussion of geographic information systems analysis. Creating crime maps and mapping other data for crime analysis is reviewed and points on privacy issues are offered. Chapter 5 presents many of the crime analysis products available for purchase, including a description of the types of administrative crime analysis reports, intelligence analysis products, and a listing of resources for crime analysis products. Chapter 6 offers advice for the new crime analyst, while chapter 7 discusses the creation of a crime analysis unit. Policies and procedures for such a unit are reviewed and the marketing and funding of a crime analysis unit are discussed. The authors describe how to Measure the success of a crime analysis unit and share crime analysis success stories. Chapter 8 moves into a discussion of education and training resources, including training options for those in law enforcement and education and training offered by colleges and universities. Finally, chapter 9 presents resources for the new crime analyst, including agency resources, publications, and Internet sites.


Crime Mapping and Spatial Data Analysis Using R

Crime Mapping and Spatial Data Analysis Using R
Author: Juanjo Medina
Publisher: CRC Press
Total Pages: 0
Release: 2023
Genre: Crime analysis
ISBN: 9780367724597

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"Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis"--