Now you can master the latest version of the fundamental SQL language used in all relational databases today with ORACLE 12C: SQL, 3E. Much more than a study guide, this edition helps you transform a basic knowledge of databases into proficiency with the latest SQL and Oracle concepts and techniques. You learn to use Oracle 12c SQL most effectively as you prepare for the first exam in the Oracle Database Administrator or Oracle Developer Certification Exam paths. This edition initially focuses on creating database objects, including tables, constraints, indexes, sequences, manipulating data, and more. The author then explores both basic data query techniques as well as advanced query topics using a proven hands-on approach. ORACLE 12C: SQL, 3E introduces the latest features and enhancements in 12c, from enhanced data types and invisible columns to new CROSS and OUTER APPLY methods for joins. To help you transition to further studies and even more advanced books in this series, appendixes introduce SQL tuning, compare Oracle's SQL syntax with other databases, and overview Oracle connection interface tools: SQL Developer and SQL Plus. Trust ORACLE 12C: SQL, 3E to provide the knowledge you need for Oracle certification testing and the solid foundation for pursuing a career as a database administrator or developer.

Preparing for a future in IT? ETHICS IN INFORMATION TECHNOLOGY, 6E provides an understanding of the legal, ethical, and societal implications of information technology that you'll need as a successful IT professional. Examine ethical situations in IT and review practical advice for addressing common issues as you study professional codes of ethics, cyberattacks and cybersecurity, security risk assessment, privacy, electronic surveillance, and freedom of expression. You also review Internet censorship, protection of intellectual property, ethical decisions in software systems, IT's impact on society, social networking, and ethics of IT corporations. This book provides a thorough foundation for addressing ethical issues in today's workplace. Business vignettes, Critical-Thinking exercises, thought-provoking Cases and decision-making features prepare you to make key business decisions.

Develop a strong understanding of IT project management as you learn to apply today's most effective project management tools and techniques with the unique approach found in Schwalbe's INFORMATION TECHNOLOGY PROJECT MANAGEMENT, 9E. Examine the latest developments and skills as you prepare for the Project Management Professional (PMP) or Certified Associate in Project Management (CAPM) exams. This edition reflects content from the latest PMBOK (R) Guide, 6E and the Agile Practice Guide while providing a meaningful context. Examples from familiar companies featured in today's news discussion, exercises and cases reinforce learning. Time-saving template files assist in completing tasks. Agile information, a guide to using Microsoft Project 2016 and MindTap online resources will help you master today's most marketable IT project management skills.

Learn the principles of MIS as you explore the latest developments and industry trends with MIS 10. This practically focused approach helps you master foundational MIS concepts that will guide your career.

You examine the latest topics, such as cloud computing, AR/VR, quantum computing and blockchain, with the most current MIS title on the market. Have you ever wondered what you would have done as a company leader in a critical moment? With this edition's MindTap digital experience, you can strengthen your decision-making skills with "YouDecide" -- new interactive case studies that bridge technology and business strategy and position you as the decision maker. You can also examine possible career paths with new career connection videos.

Delve deeper into key course concepts with new concept videos and foundational case studies. In addition, MindTap's RSS feeds alert you to the latest advancements and trends for a stronger focus on today's real business world.

In April 2021, the Court of Appeal quashed the convictions of 39 former Subpostmasters and ruled their prosecutions were an affront to the public conscience. They were just a few of the hundreds who had been prosecuted by the Post Office using IT evidence from an unreliable computer system called Horizon. When the Post Office became aware that Horizon didn't work properly, it covered it up. The Great Post Office Scandal is the story of how these innocent people had their lives ruined by a once-loved national institution and how, against overwhelming odds, they fought back to clear their names. Gripping, heart-breaking and enlightening, The Great Post Office Scandal should be read by everyone who wants to understand how this massive miscarriage of justice was allowed to happen.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

With an exciting new look, new characters to meet, and its unique combination of humour and step-by-step instruction, this award-winning book is the statistics lifesaver for everyone. From initial theory through to regression, factor analysis and multilevel modelling, Andy Field animates statistics and SPSS software with his famously bizarre examples and activities. What's brand new: A radical new design with original illustrations and even more colour A maths diagnostic tool to help students establish what areas they need to revise and improve on. A revamped online resource that uses video, case studies, datasets, testbanks and more to help students negotiate project work, master data management techniques, and apply key writing and employability skills New sections on replication, open science and Bayesian thinking Now fully up to date with latest versions of IBM SPSS Statistics (c). All the online resources above (video, case studies, datasets, testbanks) can be easily integrated into your institution's virtual learning environment or learning management system. This allows you to customize and curate content for use in module preparation, delivery and assessment. Please note that ISBN: 9781526445780 comprises the paperback edition of the Fifth Edition and the student version of IBM SPSS Statistics.

Confidently shepherd your organization's implementation of Microsoft Dynamics 365 to a successful conclusion In Mastering Microsoft Dynamics 365 Implementations, accomplished executive, project manager, and author Eric Newell delivers a holistic, step-by-step reference to implementing Microsoft's cloud-based ERP and CRM business applications. You'll find the detailed and concrete instructions you need to take your implementation project all the way to the finish line, on-time, and on-budget. You'll learn: The precise steps to take, in the correct order, to bring your Dynamics 365 implementation to life What to do before you begin the project, including identifying stakeholders and building your business case How to deal with a change management throughout the lifecycle of your project How to manage conference room pilots (CRPs) and what to expect during the sessions Perfect for CIOs, technology VPs, CFOs, Operations leaders, application directors, business analysts, ERP/CRM specialists, and project managers, Mastering Microsoft Dynamics 365 Implementations is an indispensable and practical reference for guiding your real-world Dynamics 365 implementation from planning to completion.

A Simple Guide to SPSS for Political Science, International Edition is a supplemental text that can be used with another statistics or research methods text. Designed for Political Science majors, A Simple Guide to SPSS for Political Science, International Edition helps students navigate through SPSS while taking a statistics or research methods course. The text includes additional coverage of categorical dependent variables, sample problems, and data sets specifically for Political Science. The American National Election Studies (ANES) database is used for sample problems, providing students with well-known and widely used resources in Political Science.

Become a stats superstar by using Excel to reveal the powerful secrets of statistics Microsoft Excel offers numerous possibilities for statistical analysis--and you don't have to be a math wizard to unlock them. In Statistical Analysis with Excel For Dummies, fully updated for the 2021 version of Excel, you'll hit the ground running with straightforward techniques and practical guidance to unlock the power of statistics in Excel. Bypass unnecessary jargon and skip right to mastering formulas, functions, charts, probabilities, distributions, and correlations. Written for professionals and students without a background in statistics or math, you'll learn to create, interpret, and translate statistics--and have fun doing it! In this book you'll find out how to: Understand, describe, and summarize any kind of data, from sports stats to sales figures Confidently draw conclusions from your analyses, make accurate predictions, and calculate correlations Model the probabilities of future outcomes based on past data Perform statistical analysis on any platform: Windows, Mac, or iPad Access additional resources and practice templates through Dummies.com For anyone who's ever wanted to unleash the full potential of statistical analysis in Excel--and impress your colleagues or classmates along the way--Statistical Analysis with Excel For Dummies walks you through the foundational concepts of analyzing statistics and the step-by-step methods you use to apply them.

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MIS’s easy-reference, paperback textbook presents course content through visually-engaging chapters as well as Chapter Review Cards that consolidate the best review material into a ready-made study tool. With the textbook or on its own, MIS Online allows easy exploration of MIS anywhere, anytime - including on your device! Collect your notes and create StudyBits™ from interactive content as you go to remember what’s important. Then, either use preset study resources, or personalize the product through easy-to-use tags and filters to prioritize your study time. Make and review flashcards, review related content, and track your progress with Concept Tracker, all in one place and at an affordable price!

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Most books on linear systems for undergraduates cover discrete and continuous systems material together in a single volume. Such books also include topics in discrete and continuous filter design, and discrete and continuous state-space representations. However, with this magnitude of coverage, the student typically gets a little of both discrete and continuous linear systems but not enough of either. Minimal coverage of discrete linear systems material is acceptable provided that there is ample coverage of continuous linear systems. On the other hand, minimal coverage of continuous linear systems does no justice to either of the two areas. Under the best of circumstances, a student needs a solid background in both these subjects. Continuous linear systems and discrete linear systems are broad topics and each merit a single book devoted to the respective subject matter. The objective of this set of two volumes is to present the needed material for each at the undergraduate level, and present the required material using MATLAB (R) (The MathWorks Inc.).

Master the ins and outs of Google's free-to-use office and productivity software Teach Yourself VISUALLY Google Workspace delivers the ultimate guide to getting the most out of Google's Workspace cloud software. Accomplished author Guy Hart-Davis offers readers the ability to tackle a huge number of everyday productivity problems with Google's intuitive collection of online tools. With over 700 full-color screenshots included to help you learn, you'll discover how to: Manage your online Google Calendar Master the files and folders in your Google Drive storage Customize your folders and navigate your Gmail account Create perfect spreadsheets, presentations, and documents in Google Sheets, Slides, and Docs Perfect for anyone who hopes to make sense of Google's highly practical and free online suite of tools, Teach Yourself VISUALLY Google Workspace also belongs on the bookshelves of those who already find themselves using Workspace and just want to get more out of it.

Learn how to design and develop robotic process automation solutions with Blue Prism to perform important tasks that enable value creation in your work Key Features Develop robots with Blue Prism Automate your work processes with Blue Prism Learn basic skills required to train a robot for process automation Book DescriptionRobotic process automation is a form of business process automation where user-configured robots can emulate the actions of users. Blue Prism is a pioneer of robotic process automation software, and this book gives you a solid foundation to programming robots with Blue Prism. If you've been tasked with automating work processes, but don't know where to start, this is the book for you! You begin with the business case for robotic process automation, and then move to implementation techniques with the leading software for enterprise automation, Blue Prism. You will become familiar with the Blue Prism Studio by creating your first process. You will build upon this by adding pages, data items, blocks, collections, and loops. You will build more complex processes by learning about actions, decisions, choices, and calculations. You will move on to teach your robot to interact with applications such as Internet Explorer. This can be used for spying elements that identify what your robot needs to interact with on the screen. You will build the logic behind a business objects by using read, write, and wait stages. You will then enable your robot to read and write to Excel and CSV files. This will finally lead you to train your robot to read and send emails in Outlook. You will learn about the Control Room, where you will practice adding items to a queue, processing the items and updating the work status. Towards the end of this book you will also teach your robot to handle errors and deal with exceptions. The book concludes with tips and coding best practices for Blue Prism. What you will learn Learn why and when to introduce robotic automation into your business processes Work with Blue Prism Studio Create automation processes in Blue Prism Make use of decisions and choices in your robots Use UI Automation mode, HTML mode, Region mode, and spying Learn how to raise exceptions Get the robot to deal with errors Learn Blue Prism coding best practices Who this book is forThe book is aimed at end users such as citizen developers who create business processes, but may not have the basic programming skills required to train a robot. No experience of BluePrism is required.

Like its bestselling predecessor, Multilevel Modeling Using R, Second Edition provides the reader with a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. New in the Second Edition: Features the use of lmer (instead of lme) and including the most up to date approaches for obtaining confidence intervals for the model parameters. Discusses measures of R2 (the squared multiple correlation coefficient) and overall model fit. Adds a chapter on nonparametric and robust approaches to estimating multilevel models, including rank based, heavy tailed distributions, and the multilevel lasso. Includes a new chapter on multivariate multilevel models. Presents new sections on micro-macro models and multilevel generalized additive models. This thoroughly updated revision gives the reader state-of-the-art tools to launch their own investigations in multilevel modeling and gain insight into their research. About the Authors: W. Holmes Finch is the George and Frances Ball Distinguished Professor of Educational Psychology at Ball State University. Jocelyn E. Bolin is a Professor in the Department of Educational Psychology at Ball State University. Ken Kelley is the Edward F. Sorin Society Professor of IT, Analytics and Operations and the Associate Dean for Faculty and Research for the Mendoza College of Business at the University of Notre Dame.

Whether you are preparing for a career as a business manager, computer programmer or system designer, or you simply want to be an informed home computer user, West's DATA COMMUNICATIONS AND COMPUTER NETWORKS, 9th Edition provides an understanding of the essential features, operations and limitations of today's computer networks. You learn about systems both on premises and in the cloud as the author balances technical concepts with practical, everyday issues. Updates address the latest developments and practices in cloud business principles and security techniques, software-defined networking, 5G, the Internet of Things, data analytics and supporting remote workforces. This edition also covers the CompTIA's Cloud Essentials+ exam to help you prepare for this vendor-neutral, business-oriented cloud computing certification. Hands-on learning features and thought-provoking content also guide you through virtual networking technologies, industry convergence and wired and wireless LAN technologies.

IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Output for each procedure is explained and illustrated, and every output term is defined. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS. This book covers the basics of statistical analysis and addresses more advanced topics such as multidimensional scaling, factor analysis, discriminant analysis, measures of internal consistency, MANOVA (between- and within-subjects), cluster analysis, Log-linear models, logistic regression, and a chapter describing residuals. The end sections include a description of data files used in exercises, an exhaustive glossary, suggestions for further reading, and a comprehensive index. IBM SPSS Statistics 27 Step by Step is distributed in 85 countries, has been an academic best seller through most of the earlier editions, and has proved an invaluable aid to thousands of researchers and students. New to this edition: Screenshots, explanations, and step-by-step boxes have been fully updated to reflect SPSS 27 A new chapter on a priori power analysis helps researchers determine the sample size needed for their research before starting data collection.

Highly recommended by JASA, Technometrics, and other leading statistical journals, the first two editions of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Third Edition continues to lead readers step-by-step through the process of fitting LMMs. The third edition provides a comprehensive update of the available tools for fitting linear mixed-effects models in the newest versions of SAS, SPSS, R, Stata, and HLM. All examples have been updated, with a focus on new tools for visualization of results and interpretation. New conceptual and theoretical developments in mixed-effects modeling have been included, and there is a new chapter on power analysis for mixed-effects models. Features:*Dedicates an entire chapter to the key theories underlying LMMs for clustered, longitudinal, and repeated measures data *Provides descriptions, explanations, and examples of software code necessary to fit LMMs in SAS, SPSS, R, Stata, and HLM *Contains detailed tables of estimates and results, allowing for easy comparisons across software procedures *Presents step-by-step analyses of real-world data sets that arise from a variety of research settings and study designs, including hypothesis testing, interpretation of results, and model diagnostics *Integrates software code in each chapter to compare the relative advantages and disadvantages of each package *Supplemented by a website with software code, datasets, additional documents, and updates Ideal for anyone who uses software for statistical modeling, this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures.

This book provides a general framework for learning sparse graphical models with conditional independence tests. It includes complete treatments for Gaussian, Poisson, multinomial, and mixed data; unified treatments for covariate adjustments, data integration, and network comparison; unified treatments for missing data and heterogeneous data; efficient methods for joint estimation of multiple graphical models; effective methods of high-dimensional variable selection; and effective methods of high-dimensional inference. The methods possess an embarrassingly parallel structure in performing conditional independence tests, and the computation can be significantly accelerated by running in parallel on a multi-core computer or a parallel architecture. This book is intended to serve researchers and scientists interested in high-dimensional statistics, and graduate students in broad data science disciplines. Key Features: A general framework for learning sparse graphical models with conditional independence tests Complete treatments for different types of data, Gaussian, Poisson, multinomial, and mixed data Unified treatments for data integration, network comparison, and covariate adjustment Unified treatments for missing data and heterogeneous data Efficient methods for joint estimation of multiple graphical models Effective methods of high-dimensional variable selection Effective methods of high-dimensional inference

A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.

What happens when a researcher and a practitioner spend hours crammed in a Fiat discussing data visualization? Beyond creating beautiful charts, they found greater richness in the craft as an integrated whole. Drawing from their unconventional backgrounds, these two women take readers through a journey around perception, semantics, and intent as the triad that influences visualization. This visually engaging book blends ideas from theory, academia, and practice to craft beautiful, yet meaningful visualizations and dashboards. How do you take your visualization skills to the next level? The book is perfect for analysts, research and data scientists, journalists, and business professionals. Functional Aesthetics for Data Visualization is also an indispensable resource for just about anyone curious about seeing and understanding data. Think of it as a coffee book for the data geek in you. https: //www.functionalaestheticsbook.com

Modelling Survival Data in Medical Research, Fourth Edition describes the analysis of survival data, illustrated using a wide range of examples from biomedical research. Written in a non-technical style, it concentrates on how the techniques are used in practice. Starting with standard methods for summarising survival data, Cox regression and parametric modelling, the book covers many more advanced techniques, including interval-censoring, frailty modelling, competing risks, analysis of multiple events, and dependent censoring. This new edition contains chapters on Bayesian survival analysis and use of the R software. Earlier chapters have been extensively revised and expanded to add new material on several topics. These include methods for assessing the predictive ability of a model, joint models for longitudinal and survival data, and modern methods for the analysis of interval-censored survival data. Features: Presents an accessible account of a wide range of statistical methods for analysing survival data Contains practical guidance on modelling survival data from the author's many years of experience in teaching and consultancy Shows how Bayesian methods can be used to analyse survival data Includes details on how R can be used to carry out all the methods described, with guidance on the interpretation of the resulting output Contains many real data examples and additional data sets that can be used for coursework All data sets used are available in electronic format from the publisher's website Modelling Survival Data in Medical Research, Fourth Edition is an invaluable resource for statisticians in the pharmaceutical industry and biomedical research centres, research scientists and clinicians who are analysing their own data, and students following undergraduate or postgraduate courses in survival analysis.

.".".I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)"

A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R

This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.

Includes numerous worked examples and exercises within each chapter.

Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.