The misuse of an organization's information systems by employees, whether through error or by intent, can result in leaked and corrupted data, crippled networks, lost productivity, legal problems, and public embarrassment. As organizations turn to technology to monitor employee use of network resources, they are finding themselves at odds with workers who instinctively feel their privacy is being invaded. The Visible Employee reports the results of an extensive four-year research project, covering a range of security solutions for at-risk organizations as well as the perceptions and attitudes of employees toward monitoring and surveillance. The result is a wake-up call for business owners, managers, and IT staff, as well as an eye-opening dose of reality for employees.
An Introduction to Data Science by Jeffrey S. Saltz and Jeffrey M. Stanton is an easy-to-read, gentle introduction for people with a wide range of backgrounds into the world of data science. Needing no prior coding experience or a deep understanding of statistics, this book uses the R programming language and RStudio® platform to make data science welcoming and accessible for all learners. After introducing the basics of data science, the book builds on each previous concept to explain R programming from the ground up. Readers will learn essential skills in data science through demonstrations of how to use data to construct models, predict outcomes, and visualize data.
An Introduction to Data Science by Jeffrey S. Saltz and Jeffrey M. Stanton is an easy-to-read, gentle introduction for people with a wide range of backgrounds into the world of data science. Needing no prior coding experience or a deep understanding of statistics, this book uses the R programming language and RStudio® platform to make data science welcoming and accessible for all learners. After introducing the basics of data science, the book builds on each previous concept to explain R programming from the ground up. Readers will learn essential skills in data science through demonstrations of how to use data to construct models, predict outcomes, and visualize data.
Bundled with the eBook, which will be updated regularly as new information about each virus is available, this text serves as the authoritative, up-to-date reference book for virologists, infectious disease specialists, microbiologists, and physicians, as well as medical students pursuing a career in infectious diseases.
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.
An Introduction to Data Science with Python by Jeffrey S. Saltz and Jeffery M. Stanton provides readers who are new to Python and data science with a step-by-step walkthrough of the tools and techniques used to analyze data and generate predictive models. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using Python-based Jupyter Notebooks. The techniques include making tables and data frames, computing statistics, managing data, creating data visualizations, and building machine learning models. Each chapter breaks down the process into simple steps and components so students with no more than a high school algebra background will still find the concepts and code intelligible. Explanations are reinforced with linked practice questions throughout to check reader understanding. The book also covers advanced topics such as neural networks and deep learning, the basis of many recent and startling advances in machine learning and artificial intelligence. With their trademark humor and clear explanations, Saltz and Stanton provide a gentle introduction to this powerful data science tool. Included with this title: LMS Cartridge: Import this title’s instructor resources into your school’s learning management system (LMS) and save time. Don′t use an LMS? You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
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.
Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the open-source R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using real-data examples. The companion website provides annotated R code for the book's examples, in-class exercises, supplemental reading lists, and links to online videos, interactive materials, and other resources. ÿ Pedagogical Features *Playful, conversational style and gradual approach; suitable for students without strong math backgrounds. *End-of-chapter exercises based on real data supplied in the free R package. *Technical explanation and equation/output boxes. *Appendices on how to install R and work with the sample datasets.ÿ
An Introduction to Data Science with Python by Jeffrey S. Saltz and Jeffery M. Stanton provides readers who are new to Python and data science with a step-by-step walkthrough of the tools and techniques used to analyze data and generate predictive models. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using Python-based Jupyter Notebooks. The techniques include making tables and data frames, computing statistics, managing data, creating data visualizations, and building machine learning models. Each chapter breaks down the process into simple steps and components so students with no more than a high school algebra background will still find the concepts and code intelligible. Explanations are reinforced with linked practice questions throughout to check reader understanding. The book also covers advanced topics such as neural networks and deep learning, the basis of many recent and startling advances in machine learning and artificial intelligence. With their trademark humor and clear explanations, Saltz and Stanton provide a gentle introduction to this powerful data science tool. Included with this title: LMS Cartridge: Import this title’s instructor resources into your school’s learning management system (LMS) and save time. Don′t use an LMS? You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
Provides current information on more than 5,000 legal topics. Includes completely revised articles covering important issues, biographies, definitions of legal terms and more. Covers such high-profile topics as the Americans with Disabilities Act, capital punishment, domestic violence, gay and lesbian rights, and physician-assisted suicide.
The years 1849-1877 were among the most pivotal in the nation's history. Over the course of three decades, the United States endured a catastrophic civil war, abolished slavery, expanded westward and added eight states to the Union, and witnessed the beginnings of industrialization. In politics, the era saw the demise of one national party, the birth of another, and the historic leadership of Abraham Lincoln. The country also faced difficult questions of state sovereignty and federal responsibility answered ultimately by secession and war. In short, it was a time of growth, consolidation, tragedy, and triumph for a dynamic and youthful nation. This resource of primary documents and commentary covers the Taylor through Grant administrations by selecting and describing five to ten of the foremost issues of the day and showing the actual text of the president's position along with the opposing viewpoint. The presidents from 1849-1877 were men of varied backgrounds and talents. Northerners and Southerners and even Northerners with Southern sensibilities occupied the White House. The period began and ended with war heroes as presidents; among the other men who served as president were a former textile worker, a country lawyer, and lifelong diplomat. Most of the chief executives struggled and perhaps even failed to overcome the immense challenges placed before them. By providing helpful background information and commentary about the presidents and the issues of the day in addition to the primary sources, this reference guide accurately depicts this fractious time in the country's past and provides an invaluable resources to any student of American history.
This text offers a concise single-volume survey of presidential scandals in the United States that looks at the behaviour and public image of every president from George Washington to Bill Clinton. The scandals covered include Franklin Pierce's drunkenness and JFK's extra-marital affairs.
A Politician Turned General offers a critical examination of the turbulent early political career and the controversial military service of Stephen Augustus Hurlbut, an Illinois Whig. Republican politician, and Northern political general who rose to distinction as a prominent member of the Union high command in the West during the Civil War. Though traditionally there are two different characterizations of those who exercised command during the Civil War - soldier-politician and the political generals - Hurlbut was viewed as a military politician. This book provides an important study of another friend and/or political supporter of Lincoln who rose to general during the war and gained important appointments after the war. This first biography of Hurlbut chronicles the early life and the Civil War career of one of Abraham Lincoln's foremost military appointments. Through exhaustive research of primary and secondary sources, author Jeffrey N. Lash identifies and evaluates the successes and failures of Hurlbut's generalship and combat leadership, both as a field commander in Missouri in 1861 and as a division commander at the Battles of Shiloh and Hatchie Bridge in 1862. Featuri
“A must-own title.” —National Review Online American Conservatism: An Encyclopedia is the first comprehensive reference volume to cover what is surely the most influential political and intellectual movement of the past half century. More than fifteen years in the making—and more than half a million words in length—this informative and entertaining encyclopedia contains substantive entries on those persons, events, organizations, and concepts of major importance to postwar American conservatism. Its contributors include iconic patriarchs of the conservative and libertarian movements, celebrated scholars, well-known authors, and influential movement activists and leaders. Ranging from “abortion” to “Zoll, Donald Atwell,” and written from viewpoints as various as those which have informed the postwar conservative movement itself, the encyclopedia’s more than 600 entries will orient readers of all kinds to the people and ideas that have given shape to contemporary American conservatism. This long-awaited volume is not to be missed.
With Washington's proximity to the Confederate capital of Richmond, Union military operations in the first two years of the Civil War focused mainly on the Eastern Theater, where General McClellan commanded the Army of the Potomac. McClellan's "On to Richmond" battle cry dominated strategic thinking in the high command. When he failed and was sacked by President Lincoln, a coterie of senior officers sought his return. This re-examination of the high command and McClellan's war in the East provides a broader understanding of the Union's inability to achieve victory in the first two years, and takes the debate about the Union's leadership into new areas.
Argues that social conservatism is uniquely American invention existing due to our founding principles centering on the belief that people receive equal rights from God not government.
Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the open-source R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using real-data examples. The companion website provides annotated R code for the book's examples, in-class exercises, teaching notes, and slide decks. Pedagogical Features *Playful, conversational style and gradual approach; suitable for students without strong math backgrounds. *End-of-chapter exercises based on real data supplied in the free R package. *Technical explanation and equation/output boxes. *Appendices on how to install R and work with the sample datasets.
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