Straightforward, practical guidance for working fraud examiners and forensic accountants In Data Sleuth: Using Data in Forensic Accounting Engagements and Fraud Investigations, certified fraud examiner, former FBI support employee, private investigator, and certified public accountant Leah Wietholter delivers a step-by-step guide to financial investigation that can be applied to almost any forensic accounting use-case. The book emphasizes the use of best evidence as you work through problem-solving data analysis techniques that address the common challenge of imperfect and incomplete information. The accomplished author bridges the gap between modern fraud investigation theory and practical applications and processes necessary for working practitioners. She also provides: Access to a complimentary website with supplementary resources, including a Fraud Detection Worksheet and case planning template Strategies for systematically applying the Data Sleuth® framework to streamline and grow your practice Methods and techniques to improve the quality of your work product Data Sleuth is an indispensable, hands-on resource for practicing and aspiring fraud examiners and investigators, accountants, and auditors. It’s a one-of-a-kind book that puts a practical blueprint to effective financial investigation in the palm of your hand.

Data Breach Preparation and Response: Breaches are Certain, Impact is Not is the first book to provide 360 degree visibility and guidance on how to proactively prepare for and manage a data breach and limit impact. Data breaches are inevitable incidents that can disrupt business operations and carry severe reputational and financial impact, making them one of the largest risks facing organizations today. The effects of a breach can be felt across multiple departments within an organization, who will each play a role in effectively managing the breach. Kevvie Fowler has assembled a team of leading forensics, security, privacy, legal, public relations and cyber insurance experts to create the definitive breach management reference for the whole organization. Discusses the cyber criminals behind data breaches and the underground dark web forums they use to trade and sell stolen data Features never-before published techniques to qualify and discount a suspected breach or to verify and precisely scope a confirmed breach Helps identify your sensitive data, and the commonly overlooked data sets that, if stolen, can result in a material breach Defines breach response plan requirements and describes how to develop a plan tailored for effectiveness within your organization Explains strategies for proactively self-detecting a breach and simplifying a response Covers critical first-responder steps and breach management practices, including containing a breach and getting the scope right, the first time Shows how to leverage threat intelligence to improve breach response and management effectiveness Offers guidance on how to manage internal and external breach communications, restore trust, and resume business operations after a breach, including the critical steps after the breach to reduce breach-related litigation and regulatory fines Illustrates how to define your cyber-defensible position to improve data protection and demonstrate proper due diligence practices

The use of data science and urban analytics has become a defining feature of smart cities. This timely book is a clear guide to the use of social media data for urban analytics. The book presents the foundations of urban analytics with social media data, along with real-world applications and insights on the platforms we use today. It looks at social media analytics platforms, cyberphysical data analytics platforms, crowd detection platforms, City-as-a-Platform, and city-as-a-sensor for platform urbanism. The book provides examples to illustrate how we apply and analyse social media data to determine disaster severity, assist authorities with pandemic policy, and capture public perception of smart cities. This will be a useful reference for those involved with and researching social, data, and urban analytics and informatics.

Prepare for exams and succeed in your statistics course with this comprehensive solutions manual! Featuring worked out-solutions to the problems in THE STATISTICAL SLEUTH: A COURSE IN METHODS OF DATA ANALYSIS, 2nd Edition, this manual shows you how to approach and solve problems using the same step-by-step explanations found in your textbook examples.

Presents modern methods to analyzing data with multiple applications in a variety of scientific fields Written at a readily accessible level, Basic Data Analysis for Time Series with R emphasizes the mathematical importance of collaborative analysis of data used to collect increments of time or space. Balancing a theoretical and practical approach to analyzing data within the context of serial correlation, the book presents a coherent and systematic regression-based approach to model selection. The book illustrates these principles of model selection and model building through the use of information criteria, cross validation, hypothesis tests, and confidence intervals. Focusing on frequency- and time-domain and trigonometric regression as the primary themes, the book also includes modern topical coverage on Fourier series and Akaike's Information Criterion (AIC). In addition, Basic Data Analysis for Time Series with R also features: Real-world examples to provide readers with practical hands-on experience Multiple R software subroutines employed with graphical displays Numerous exercise sets intended to support readers understanding of the core concepts Specific chapters devoted to the analysis of the Wolf sunspot number data and the Vostok ice core data sets

With the increasing number of neuroimaging studies appearing yearly in the literature, the need to consider the synthesis of the underlying data into new knowledge and research directions has never been more important. The development of large-scale databases and grid-enabled computing has laid the groundwork for mining these rich datasets beyond the scope of their initial collection. Additionally, meta-analyses of the summary results contained in published research articles have provided a powerful way to explore hidden trends in the neuroscience literature. In each case, the processing of data requires a careful consideration of the individual processing steps involved and how they can be assembled into reliable workflows. In results from published studies, the manner in which data were processed may influence meta-analytic results which can have implications on clinical interpretation. Several efforts now exist that provide tools for use in the construction of data processing workflows. However, careful thought must be given to ensuring appropriate, efficient, optimal, and replicable processing. The results obtained from data-mining and meta-analysis must tell a story about a collection of existing data. Also they must suggest novel and testable hypotheses for further investigation with implications for understanding of the brain in health and disease. Where they do, these new results and interpretations often provide fresh insights into the data that extend beyond the rationale for their original collection. In this volume, we have asked leaders in the field of neuroimaging data mining and meta-analysis to provide their thoughts on methods for efficient workflow design, interoperability with large-scale databases, and to discuss their work in exploring the richness of brain imaging data as well as the literature of published research results.

Unleash the power of data by creating interactive, engaging, and compelling visualizations for the web About This Book Get a portable, versatile, and flexible data visualization design approach that will help you navigate the complex path towards success Get thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options A comprehensive and contemporary introduction to data-driven visualization design and the most effective approaches to designing impact-maximizing and cognition-amplifying visualizations Who This Book Is For This course is for developers who are excited about data and who want to share that excitement with others and it will be handy for the web developers or data scientists who want to create interactive visualizations for the web. Prior knowledge of developing web applications is required. You should have a working knowledge of both JavaScript and HTML. What You Will Learn Harness the power of D3 by building interactive and real-time data-driven web visualizations Find out how to use JavaScript to create compelling visualizations of social data Identify the purpose of your visualization and your project's parameters to determine overriding design considerations across your project's execution Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics Explore the various features of HTML5 to design creative visualizations Discover what data is available on Stack Overflow, Facebook, Twitter, and Google+ Gain a solid understanding of the common D3 development idioms Find out how to write basic D3 code for server using Node.js In Detail Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories, and key insights that are locked away. This learning path is divided into three modules. The first module will equip you with the key techniques required to overcome contemporary data visualization challenges. After getting familiar with key concepts of data visualization, it's time to incorporate it with various technologies. In the second module, Social Data Visualization with HTML5 and JavaScript, it teaches you how to leverage HTML5 techniques through JavaScript to build visualizations. It also clears up how the often complicated OAuth protocol works to help you unlock a universe of social media data from sites such as Twitter, Facebook, and Google+. Once you are familiar with the concepts of incorporating data visualization with HTML5 and JavaScript, third module, Learning d3.js Data Visualization, will lead you to D3, which has emerged as one of the leading platforms to develop beautiful, interactive visualizations over the web. This module provides a strong foundation in designing compelling web visualizations with D3.js. By the end of this course, you will have unlocked the mystery behind successful data visualizations. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Data Visualization: a successful design process by Andy Kirk Social Data Visualization with HTML5 and JavaScript by Simon Timms Learning d3.js Data Visualization, Second Edition by Ǯdrew Rininsland and Swizec Teller Style and approach This course includes all the resources that will help you jump into creating interactive and engaging visualizations for the web. Through this comprehensive course, you'll learn how to create engaging visualizations for the web to represent your data from start to finish!

This invaluable professional resource instructs teachers on how to successfully implement Guided Math Workstations into grades 6-8 classrooms. With detailed instructions that are easily adopted into today's classrooms, this book contains everything teachers need to set up, plan, and manage workstations. Guided Math Workstations allow teachers to address their students' varied learning needs within a carefully planned numeracy-rich environment where students are challenged to not just do math, but to become mathematicians. Teachers will be able to successfully target the specific needs of learners with small-group lessons as students work independently on math workstation tasks. Each workstation task includes: an overview of the lesson, materials, objective, procedure, and differentiation tactics; a Student Task card with directions and a materials list for the task to help with implementation and organization; a Talking Points card with math vocabulary words and sentence stems to encourage mathematical discourse; and additional resources for each task.

THE STATISTICAL SLEUTH: A COURSE IN METHODS OF DATA ANALYSIS, Third Edition offers an appealing treatment of general statistical methods that takes full advantage of the computer, both as a computational and an analytical tool. The material is independent of any specific software package, and prominently treats modeling and interpretation in a way that goes beyond routine patterns. The book focuses on a serious analysis of real case studies, strategies and tools of modern statistical data analysis, the interplay of statistics and scientific learning, and the communication of results. With interesting examples, real data, and a variety of exercise types (conceptual, computational, and data problems), the authors get students excited about statistics. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

How the hidden trade in our sensitive medical information became a multibillion-dollar business, but has done little to improve our health-care outcomes Hidden to consumers, patient medical data has become a multibillion-dollar worldwide trade industry between our health-care providers, drug companies, and a complex web of middlemen. This great medical-data bazaar sells copies of the prescription you recently filled, your hospital records, insurance claims, blood-test results, and more, stripped of your name but possibly with identifiers such as year of birth, gender, and doctor. As computing grows ever more sophisticated, patient dossiers become increasingly vulnerable to reidentification and the possibility of being targeted by identity thieves or hackers. Paradoxically, comprehensive electronic files for patient treatment—the reason medical data exists in the first place—remain an elusive goal. Even today, patients or their doctors rarely have easy access to comprehensive records that could improve care. In the evolution of medical data, the instinct for profit has outstripped patient needs. This book tells the human, behind-the-scenes story of how such a system evolved internationally. It begins with New York advertising man Ludwig Wolfgang Frohlich, who founded IMS Health, the world’s dominant health-data miner, in the 1950s. IMS Health now gathers patient medical data from more than 45 billion transactions annually from 780,000 data feeds in more than 100 countries. Our Bodies, Our Data uncovers some of Frohlich’s hidden past and follows the story of what happened in the following decades. This is both a story about medicine and medical practice, and about big business and maximizing profits, and the places these meet, places most patients would like to believe are off-limits. Our Bodies, Our Data seeks to spark debate on how we can best balance the promise big data offers to advance medicine and improve lives while preserving the rights and interests of every patient. We, the public, deserve a say in this discussion. After all, it’s our data.