A Guide to Doing Statistics in Second Language Research Using SPSS and R, Second Edition is the only text available that demonstrates how to use SPSS and R as specifically related to applied linguistics and SLA research. This new edition is up-to-date with the most recent version of the SPSS software and now also includes coverage of R, a software program increasingly used by researchers in this field. Supported by a number of pedagogical features, including tip boxes and practice activities, and a wealth of screenshots, this book takes readers through each step of performing and understanding statistical research, covering the most commonly used tests in second language research, including t-tests, correlation, and ANOVA. A robust accompanying website covers additional tests of interest to students and researchers, taking them step-by-step through carrying out these tests themselves. In this comprehensive and hands-on volume, Jenifer Larson-Hall equips readers with a thorough understanding and the practical skills necessary to conducting and interpreting statisical research effectively using SPSS and R, ideal for graduate students and researchers in SLA, social sciences, and applied lingustics. For more information and materials, please visit www.routledge.com/cw/larson-hall.

DESCRIPTION R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data. R in Action, Second Edition is language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that real data analysts use to acquire their data, get it into shape, analyze it, and produce meaningful results that they can provide to clients. RETAIL SELLING POINTS Step-by-step guide to practical data analysis Gives quick access to the R language Written by seasoned researcher Uses over 130 graphics AUDIENCE This book is for social scientists, medical and pharmaceutical researchers, professors and students in quantitative fields, data analysts, data mining specialists, and statistical programmers who have a sense of what they want to do, but not how to do it in R. ABOUT THE TECHNOLOGY R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standard, complex data formats, such as robot logs and email messages Text processing and regular expressions Newer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google Earth Statistical methods, such as classification trees, k-nearest neighbors, and naive Bayes Visualization and exploratory data analysis Relational databases and Structured Query Language (SQL) Simulation Algorithm implementation Large data and efficiency Suitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data. Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers' computational reasoning of real-world data analyses.

Corporations and governmental agencies of all sizes are embracing a new generation of enterprise-scale business intelligence (BI) and data warehousing (DW), and very often appoint a single senior-level individual to serve as the Enterprise BI/DW Program Manager. This book is the essential guide to the incremental and iterative build-out of a successful enterprise-scale BI/DW program comprised of multiple underlying projects, and what the Enterprise Program Manager must successfully accomplish to orchestrate the many moving parts in the quest for true enterprise-scale business intelligence and data warehousing. Author Alan Simon has served as an enterprise business intelligence and data warehousing program management advisor to many of his clients, and spent an entire year with a single client as the adjunct consulting director for a $10 million enterprise data warehousing (EDW) initiative. He brings a wealth of knowledge about best practices, risk management, organizational culture alignment, and other Critical Success Factors (CSFs) to the discipline of enterprise-scale business intelligence and data warehousing.

Designed to introduce students to quantitative methods in a way that can be applied to all kinds of data in all kinds of situations, Statistics and Data Visualization Using R: The Art and Practice of Data Analysis by David S. Brown teaches students statistics through charts, graphs, and displays of data that help students develop intuition around statistics as well as data visualization skills. By focusing on the visual nature of statistics instead of mathematical proofs and derivations, students can see the relationships between variables that are the foundation of quantitative analysis. Using the latest tools in R and R RStudio (R) for calculations and data visualization, students learn valuable skills they can take with them into a variety of future careers in the public sector, the private sector, or academia. Starting at the most basic introduction to data and going through most crucial statistical methods, this introductory textbook quickly gets students new to statistics up to speed running analyses and interpreting data from social science research.

The emphasis of the book is given in how to construct different types of solutions (exact, approximate analytical, numerical, graphical) of numerous nonlinear PDEs correctly, easily, and quickly. The reader can learn a wide variety of techniques and solve numerous nonlinear PDEs included and many other differential equations, simplifying and transforming the equations and solutions, arbitrary functions and parameters, presented in the book). Numerous comparisons and relationships between various types of solutions, different methods and approaches are provided, the results obtained in Maple and Mathematica, facilitates a deeper understanding of the subject. Among a big number of CAS, we choose the two systems, Maple and Mathematica, that are used worldwide by students, research mathematicians, scientists, and engineers. As in the our previous books, we propose the idea to use in parallel both systems, Maple and Mathematica, since in many research problems frequently it is required to compare independent results obtained by using different computer algebra systems, Maple and/or Mathematica, at all stages of the solution process. One of the main points (related to CAS) is based on the implementation of a whole solution method (e.g. starting from an analytical derivation of exact governing equations, constructing discretizations and analytical formulas of a numerical method, performing numerical procedure, obtaining various visualizations, and comparing the numerical solution obtained with other types of solutions considered in the book, e.g. with asymptotic solution).

Instead of presenting the standard theoretical treatments that underlie the various numerical methods used by scientists and engineers, Using R for Numerical Analysis in Science and Engineering shows how to use R and its add-on packages to obtain numerical solutions to the complex mathematical problems commonly faced by scientists and engineers. This practical guide to the capabilities of R demonstrates Monte Carlo, stochastic, deterministic, and other numerical methods through an abundance of worked examples and code, covering the solution of systems of linear algebraic equations and nonlinear equations as well as ordinary differential equations and partial differential equations. It not only shows how to use R's powerful graphic tools to construct the types of plots most useful in scientific and engineering work, but also: Explains how to statistically analyze and fit data to linear and nonlinear models Explores numerical differentiation, integration, and optimization Describes how to find eigenvalues and eigenfunctions Discusses interpolation and curve fitting Considers the analysis of time series Using R for Numerical Analysis in Science and Engineering provides a solid introduction to the most useful numerical methods for scientific and engineering data analysis using R.

Take an in-depth look at SAP SuccessFactors talent modules with this complete guide to configuration, administration, and best practices. This two-volume series follows a logical progression of SAP SuccessFactors modules that should be configured to complete a comprehensive talent management solution. The authors walk you through fully functional simple implementations in the primary chapters for each module before diving into advanced topics in subsequent chapters. In volume 2, you will explore the development module in three more chapters by learning to configure and use development plans, career worksheets, and mentoring. Then, the book examines succession management, covering topics such as configuring, administering, and using the 9-box, the Talent Review form, nominations, succession org charts, talent pools, and succession presentations. The authors then sum up with a review of what you learned and final conclusions. Within each topic, the book touches on the integration points with other modules as well as internationalization. The authors also provide recommendations and insights from real world experience. Having finished the book, you will have an understanding of what comprises a complete SAP SuccessFactors talent management solution and how to configure, administer, and use each module within it. What You Will Learn Work with the career worksheet Build mentoring into your SAP SuccessFactors solution Display and update relevant talent data in a succession org chart Who This Book Is For Implementation partners and customers who are project managers, configuration specialists, analysts, or system administrators.

Get your first channel up and running quickly and understand how to grow your marketing initiatives as you need or want to expand your reach with mailchimp Key Features * Learn how to move quickly to establish your first marketing channel * Begin to reduce trial and error of experimenting by yourself * Understand various use-cases depending on the type of business you might have Book Description Readers will start by understanding how and why to use the Mailchimp Platform. Understand common terms used in Mailchimp enviornment. the nuanced differences between groups, tags, and segments and how they can be used throughout the platform. Additionally, the chapter will go into how these can be used when your contacts are subscribing to automate the creation of some of these contact subsets. Then the book covers the two basic channels and how to set the tone for your marketing and outreach to your contacts. We will review what we should consider the role of templates to be in your marketing strategy and how to think about what might be consistent within their marketing attempts (things like logo, openings, footers, etc.). Then the section will go into how to leverage this in your campaign sends and how to think about timing and your audience and their locations in terms of engagement. to set up a consistent marketing presence in the form of websites and the benefits of determining a brand identity. Then they will learn to optimize the platform utilization and expand on analytic options and even some pro features for leveraging comparative reports. Later, they will be in a position to understand benefits of integrating their external commerce platform to their marketing initiatives if they do so. What you will learn * Take ownership of designing your marketing voice and mechanism * Learn to grow your marketing initiatives as you need or want to expand your reach * Learn to make informed decisions about the marketing channels relevant to your business goals * Begin to experiment with at least one channel to better grow or understand your audience * Learn to progress to automating your marketing efforts quickly * Empowering yourself to have more time and put in additional efforts on other parts of your business Who This Book Is For If you are a small-to-midsize business or an entrepreneur who is just starting their marketing journey and enjoys researching engagement strategies this book is for you. In order to get the best from this book you just need to be familiar with leveraging web-apps and have a notion of content design. This book will help readers to take hands-on initial ownership of designing their marketing voice and mechanisms.

"Managing Data in Motion" describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment.

The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired.

The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. "Managing Data in Motion" tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects.
Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data typesExplains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"

Applied Numerical Methods for Chemical Engineers emphasizes the derivation of a variety of numerical methods and their application to the solution of engineering problems, with special attention to problems in the chemical engineering field. These algorithms encompass linear and nonlinear algebraic equations, eigenvalue problems, finite difference methods, interpolation, differentiation and integration, ordinary differential equations, boundary value problems, partial differential equations, and linear and nonlinear regression analysis. MATLAB is adopted as the calculation environment throughout the book because of its ability to perform all the calculations in matrix form, its large library of built-in functions, its strong structural language, and its rich graphical visualization tools. Through this book, students and other users will learn about the basic features, advantages and disadvantages of various numerical methods, learn and practice many useful m-files developed for different numerical methods in addition to the MATLAB built-in solvers, develop and set up mathematical models for problems commonly encountered in chemical engineering, and solve chemical engineering related problems through examples and after-chapter problems with MATLAB by creating application m-files.

Are you running your business or is it running you? Running a small business can take over your life but it doesn't have to be that way. Choosing and using the right technology and systems can transform the way your business works and this book shows you how! No matter how technophobic you are, Sorted! will quickly help you find the small changes that will make a big difference to your business. If you're more tech savvy, you'll love the ninja tips to take your business to the next level. Feel more confident in your choice of technology and systems for the future, because whatever your plans are, you need the right systems in place to help you achieve them.

Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, extending to classical methods and successively leading to advances in this field. Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful for the audience working in different disciplines in academics, research and industry in areas concerning to process monitoring, fault diagnosis, control and related disciplines.

Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.

In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics. An Introduction to Bioinformatics with R: A Practical Guide for Biologists leads the reader through the basics of computational analysis of data encountered in modern biological research. With no previous experience with statistics or programming required, readers will develop the ability to plan suitable analyses of biological datasets, and to use the R programming environment to perform these analyses. This is achieved through a series of case studies using R to answer research questions using molecular biology datasets. Broadly applicable statistical methods are explained, including linear and rank-based correlation, distance metrics and hierarchical clustering, hypothesis testing using linear regression, proportional hazards regression for survival data, and principal component analysis. These methods are then applied as appropriate throughout the case studies, illustrating how they can be used to answer research questions. Key Features: * Provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. * Describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook, from basic principles * Presents walk-throughs of data analysis tasks using R and example datasets. All R commands are presented and explained in order to enable the reader to carry out these tasks themselves. * Uses outputs from a large range of molecular biology platforms including DNA methylation and genotyping microarrays; RNA-seq, genome sequencing, ChIP-seq and bisulphite sequencing; and high-throughput phenotypic screens. * Gives worked-out examples geared towards problems encountered in cancer research, which can also be applied across many areas of molecular biology and medical research. This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. It is appropriate for use as a textbook or as a practical book for biological scientists looking to gain bioinformatics skills.

Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative -omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries.

The thoroughly updated and rewritten edition analyses and explains the applications of financial accounting. Divided into 15 chapters, the text elucidates, with the help of tables, boxes and practical examples, all basic accounting principles. Keeping the students without accounting background into consideration, the book highlights the use of jargon-free language in a student-friendly manner so that they can comprehend the subject with great ease. The book is intended primarily for the postgraduate students of management, and also, for the students preparing for CA, CS and ICWA. Besides, practising managers should find this book handy for analysing financial statements. Highlights Of The Fifth Edition Ind AS revised up to April 30, 2019 Schedule III of the Companies Act, 2013 Numerous illustrations and solved problems to enable students to master the concepts Chapter-wise Solutions to Assignments at the end of the book Adequate study material that is a must for the management students in their first course

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code

Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to eHealth and Patient Data Monitoring presents advanced processing techniques for IoT data streams and the anomaly detection algorithms over them. The book brings new advances and generalized techniques for processing IoT data streams, semantic data enrichment with contextual information at Edge, Fog and Cloud as well as complex event processing in IoT applications. The book comprises fundamental models, concepts and algorithms, architectures and technological solutions as well as their application to eHealth. Case studies, such as the bio-metric signals stream processing are presented -the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches including the Hierarchical Temporal Memory and Deep Learning algorithms. The book discusses adaptive solutions to IoT stream processing that can be extended to different use cases from different fields of eHealth, to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenarios. The book ends with a discussion on ethics, emerging research trends, issues and challenges of IoT data stream processing.

This is a new edition of the accessible and student-friendly 'how to' for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from 'zero to hero', updating the now standard text to further enable practical R applications in GIS, spatial analyses, spatial statistics, web-scraping and more. Revised and updated, each chapter includes: example data and commands to explore hands-on; scripts and coding to exemplify specific functionality; self-contained exercises for students to work through; embedded code within the descriptive text. The new edition includes detailed discussion of new and emerging packages within R like sf, ggplot, tmap, making it the go to introduction for all researchers collecting and using data with location attached. This is the introduction to the use of R for spatial statistical analysis, geocomputation, and GIS for all researchers - regardless of discipline - collecting and using data with location attached.

AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture. Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming.

Get to work in SAP S/4HANA with this introductory guide! Learn how to navigate your user interface, manage and report on your data, customize your reports, and tailor the system to your preferences. Then walk through daily tasks for several key lines of business: procurement, sales, and finance. With details on special functions and troubleshooting, this is the complete guide to your SAP S/4HANA workday! In this book, you'll learn about: a. User Operations Get started in your new system! Learn how to log in, navigate, and display, maintain, and report on your company's data. b. Customization Options Use SAP S/4HANA according to your specifications and preferences! Adapt your reporting settings and personalize your user interface so that it works for you, whether you're using the new UI (SAP Fiori) or the classic look of SAP GUI. c. Business Processes See how to complete day-to-day tasks in key lines of business. Perform procurement activities in materials management, ordering and invoicing in sales, and business transactions in finance such as displaying open items or a balance sheet. Highlights Include: 1) Logon and navigation 2) Reporting 3) Personalization 4) Procurement 5) Sales 6) Financial accounting 7) Special functions 8) Troubleshooting 9) SAP Fiori applications 10) SAP GUI transactions

Environmentally Sustainable Corrosion Inhibitors: Fundamentals and Industrial Applications covers the latest research developments in environmentally friendly, sustainable corrosion inhibitors. The book addresses the fundamental characteristics, synthesis, characterization and mechanisms of corrosion inhibitors. In addition, it presents a chronological overview of the growth of the field, with numerous examples of its broad-ranging industrial applications in a.o. food, the environment, electronics, and the oil and gas industries. The book concludes with discussions about commercialization and economics. This is an indispensable reference for chemical engineers and chemists working in R&D and academia who want to learn more about environmentally-friendly, sustainable corrosion inhibitors systems.

Throughout the world, high-profile large organizations (aerospace and defense, automotive, banking, chemicals, financial service providers, healthcare, high tech, insurance, oil and gas, pharmaceuticals, retail, telecommunications, and utilities) and governments are using SAP software to process their most mission-critical, highly sensitive data. With more than 100,000 installations, SAP is the world's largest enterprise software company and the world's third largest independent software supplier overall.
Despite this widespread use, there have been very few books written on SAP implementation and security, despite a great deal of interest. (There are 220,000 members in an on-line SAP 'community' seeking information, ideas and tools on the IT Toolbox Website alone.) Managing SAP user authentication and authorizations is becoming more complex than ever, as there are more and more SAP products involved that have very different access issues. It's a complex area that requires focused expertise.
This book is designed for these network and systems administrator who deal with the complexity of having to make judgmental decisions regarding enormously complicated and technical data in the SAP landscape, as well as pay attention to new compliance rules and security regulations.
Most SAP users experience significant challenges when trying to manage and mitigate the risks in existing or new security solutions and usually end up facing repetitive, expensive re-work and perpetuated compliance challenges. This book is designed to help them properly and efficiently manage these challenges on an ongoing basis. It aims to remove the 'Black Box' mystique that surrounds SAP security.
* The most comprehensive coverage of the essentials of SAP security currently available: risk and control management, identity and access management, data protection and privacy, corporate governance, legal and regulatory compliance.
* This book contains information about SAP security that is not available anywhere else to help the reader avoid the "gotchas" that may leave them vulnerable during times of upgrade or other system changes
*Companion Web site provides custom SAP scripts, which readers can download to install, configure and troubleshoot SAP.

Understanding Statistics in Psychology with SPSS, eighth edition, offers students a trusted, straightforward, and engaging way of learning to do statistical analyses confidently using SPSS. Comprehensive and practical, the text is organised into short accessible chapters, making it the ideal text for undergraduate psychology students needing to get to grips with statistics in class or independently. Clear diagrams and full colour screenshots from SPSS make the text suitable for beginners while the broad coverage of topics ensures that students can continue to use it as they progress to more advanced techniques. Key features * Combines coverage of statistics with full guidance on how to use SPSS to analyse data. * Suitable for use with all versions of SPSS. * Examples from a wide range of real psychological studies illustrate how statistical techniques are used in practice. * Includes clear and detailed guidance on choosing tests, interpreting findings and reporting and writing up research. * Student-focused pedagogical approach including: o Key concept boxes detailing important terms. o Focus on sections exploring complex topics in greater depth. o Explaining statistics sections clarify important statistical concepts. . Dennis Howitt and Duncan Cramer are with Loughborough University.