Inspired by the author's need for practical guidance in the processes of data analysis, "A Practical Guide to Scientific Data Analysis" has been written as a statistical companion for the working scientist. This handbook of data analysis with worked examples focuses on the application of mathematical and statistical techniques and the interpretation of their results.

Covering the most common statistical methods for examining and exploring relationships in data, the text includes extensive examples from a variety of scientific disciplines.

The chapters are organised logically, from planning an experiment, through examining and displaying the data, to constructing quantitative models. Each chapter is intended to stand alone so that casual users can refer to the section that is most appropriate to their problem.

Written by a highly qualified and internationally respected author this text: Presents statistics for the non-statisticianExplains a variety of methods to extract information from dataDescribes the application of statistical methods to the design of "performance chemicals"Emphasises the application of statistical techniques and the interpretation of their results

Of practical use to chemists, biochemists, pharmacists, biologists and researchers from many other scientific disciplines in both industry and academia.

A self-contained introduction to abstract interpretation-based static analysis, an essential resource for students, developers, and users. Static program analysis, or static analysis, aims to discover semantic properties of programs without running them. It plays an important role in all phases of development, including verification of specifications and programs, the synthesis of optimized code, and the refactoring and maintenance of software applications. This book offers a self-contained introduction to static analysis, covering the basics of both theoretical foundations and practical considerations in the use of static analysis tools. By offering a quick and comprehensive introduction for nonspecialists, the book fills a notable gap in the literature, which until now has consisted largely of scientific articles on advanced topics. The text covers the mathematical foundations of static analysis, including semantics, semantic abstraction, and computation of program invariants; more advanced notions and techniques, including techniques for enhancing the cost-accuracy balance of analysis and abstractions for advanced programming features and answering a wide range of semantic questions; and techniques for implementing and using static analysis tools. It begins with background information and an intuitive and informal introduction to the main static analysis principles and techniques. It then formalizes the scientific foundations of program analysis techniques, considers practical aspects of implementation, and presents more advanced applications. The book can be used as a textbook in advanced undergraduate and graduate courses in static analysis and program verification, and as a reference for users, developers, and experts.

Evolve the humble CLI with Go and unleash the next generation of powerful, flexible, empathy-driven interfaces. Finally, join a community of other CLI developers and distribute within the popular Homebrew package management tool! Key Features * Discover how Go enables the development of powerful, elegant, and intuitive CLIs * Explore a range of CLI development aspects and pick up a vast array of best practices * Create impressive interfaces that are both fun and user-friendly, and learn how to distribute them Book Description Let's face it: GUIs can only do so much. Sure, they have their place - they're intuitive and user-friendly - but for productivity, nothing beats a CLI. Many organizations these days settle for the GUI, thinking no alternative offers similar accessibility but better functionality. Does this describe your organization? Pick up this book and get them to think again. Building Modern CLI Applications in Go helps you achieve what most assume isn't possible: an interface that rivals the GUI in elegance yet surpasses it in high-performance execution. Through its practical, step-by-step approach, you'll gain everything you need to harness the power and simplicity of the Go language to build CLI applications that revolutionize the way you work. After a primer on CLI standards and Go, you'll be launched into tool design and proper framework use for true development proficiency. The book then moves on to all things CLI, giving you full mastery of everything from arguments and flags to errors and API calls. Later, you'll dive into the nuances of empathic development, so that you can ensure the best UX possible, before you finish up with build tags, cross-compilation, and container-based distribution. By the end of this guide, you'll be fully equipped to take the performance and flexibility of your organization's applications to the next level. What you will learn * Explore good CLI philosophy and enact it effectively using Go * Master Go code structure, testing, and other essentials * Add a colorful dashboard to your CLI using engaging ASCII banners * Use Cobra, Viper, and other frameworks to give your CLI an edge * Handle inputs, API commands, errors, and timeouts like a pro * Target builds for specific platforms the right way using build tags * Build with empathy, using easy bug submission and traceback * Containerize, distribute, and publish your CLIs quickly and easily Who This Book Is For This book is for beginner and intermediate Golang developers who have an interest in developing CLIs and who enjoy learning by doing. You will need to understand basic Golang programming concepts but will require no prior knowledge of CLI design and development.

Stress Testing and Risk Integration in Banks provides a comprehensive view of the risk management activity by means of the stress testing process. An introduction to multivariate time series modeling paves the way to scenario analysis in order to assess a bank resilience against adverse macroeconomic conditions. Assets and liabilities are jointly studied to highlight the key issues that a risk manager needs to face. A multi-national bank prototype is used all over the book for diving into market, credit, and operational stress testing. Interest rate, liquidity and other major risks are also studied together with the former to outline how to implement a fully integrated risk management toolkit. Examples, business cases, and exercises worked in Matlab and R facilitate readers to develop their own models and methodologies.

The modern world is awash with data. The R Project is a statistical environment and programming language that can help to make sense of it all. A huge open-source project, R has become enormously popular because of its power and flexibility. With R you can organise, analyse and visualise data. This clear and methodical book will help you learn how to use R from the ground up, giving you a start in the world of data science. Learning about data is important in many academic and business settings, and R offers a potent and adaptable programming toolbox. The book covers a range of topics, including: importing/exporting data, summarising data, visualising data, managing and manipulating data objects, data analysis (regression, ANOVA and association among others) and programming functions. Regardless of your background or specialty, you'll find this book the perfect primer on data analysis, data visualisation and data management, and a springboard for further exploration.

IBM SPSS Statistics 26 Step by Step: A Simple Guide and Reference, sixteenth 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 multi-dimensional 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. Back matter includes a description of data files used in exercises, an exhaustive glossary, suggestions for further reading and a comprehensive index. IMB SPSS Statistics 26 Step by Step is distributed in 85 countries, has been an academic best seller through most of the earlier editions, and has proved 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 26 How to handle missing data has been revised and expanded and now includes a detailed explanation of how to create regression equations to replace missing data More explicit coverage of how to report APA style statistics; this primarily shows up in the Output sections of Chapters 6 through 16, though changes have been made throughout the text.

Building SPSS Graphs to Understand Data is for anyone needing to understand large or small amounts of data. It describes how to build and interpret graphs, showing how understanding data means that the graph must clearly and succinctly answer questions about the data. In 16 of the 19 chapters research questions are presented, and the reader builds the appropriate graph needed to answer the questions. This handy guide can be used in conjunction with any introductory or intermediate statistics book where the focus is on in-depth presentation of how graphs are used. This book will also useful for graduate students doing research at the masters or doctoral level. The book also contains a chapter designed to address many of the ways that graphs can be used to mislead the graph reader.

Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world. The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect. Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more. Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.

Ideal for researchers and graduate students in the social sciences who require knowledge of structural equation modeling techniques to answer substantive research questions, Using Mplus for Structural Equation Modeling provides a reader-friendly introduction to the major types of structural equation models implemented in the Mplus framework. This practical book, which updates author E. Kevin Kelloway's 1998 book Using LISREL for Structural Equation Modeling, retains the successful five-step process employed in the earlier book, with a thorough update for use in the Mplus environment. Kelloway provides an overview of structural equation modeling techniques in Mplus, including the estimation of confirmatory factor analysis and observed variable path analysis. He also covers multilevel modeling for hypothesis testing in real life settings and offers an introduction to the extended capabilities of Mplus, such as exploratory structural equation modeling and estimation and testing of mediated relationships. A sample application with the source code, printout, and results is presented for each type of analysis.

This book is designed as a student handout for a two-day training course and may also be used as a self-teach book. This course objectives are to teach participants: * The user interface, * How to create a projects, * Scheduling projects without resources, * Filters, Views, Sorts and Printing, * Creating and assigning a baseline and * Updating an un-resourced project. Most chapters are reinforced by student workshops.

Avoid implementation failures and technical debt by mitigating anti-patterns in your Salesforce enterprise solutions using expert guidance and proven recommendations Purchase of the print or Kindle book includes a free eBook PDF Key Features Build exemplary Salesforce architectures by studying anti-patterns that lead to failing systems Demonstrate deep architectural principles that you can apply in your Salesforce projects Identify common problems in Salesforce architectures and apply better architectural solutions Book DescriptionSalesforce Anti-Patterns teaches you to spot errors in Salesforce patterns that may seem like a good idea at first but end up costing you dearly. This book will enable Salesforce developers and architects to understand how ingenious Salesforce architectures can be created by studying anti-patterns and solutions to problems that can later lead to serious implementation issues. While there are several books on the market that start with the question, "How do I create great Salesforce architecture?" and proceed to a solution from there, this book instead starts by asking, "What tends to go wrong with Salesforce architectures?" and proceeds to a solution from there. In this book, you'll find out how to identify and mitigate anti-patterns in the technical domains of system architecture, data architecture, and security architecture, along with anti-patterns in the functional domain of solution architecture as well as for integration architecture. You'll also learn about common anti-patterns affecting your Salesforce development process and governance and, finally, how to spot common problems in how architects communicate their solutions. By the end of this Salesforce book, you'll have gained the confidence to architect and communicate solutions on the Salesforce platform while dodging common mistakes. What you will learn Create a balanced system architecture by identifying common mistakes around on- and off-platform functionality and interfaces Avoid security problems that arise from anti-patterns on the Salesforce platform Spot common data architecture issues and discover intuitive ways to address them Avoid the dual traps of over- and under-customization in your solution architecture Explore common errors made in deployment setups, test strategy, and architecture governance Understand why bad communication patterns are so overlooked in architecture Who this book is forThis book is for Salesforce architects, aspiring architects, developers, consultants, and decision makers who want to start making the right architectural choices or prepare for their journey to CTA. This book helps you gain a professional understanding of Salesforce and its building blocks. It is not code-centric, so you will benefit from both functional and technical experience, but a basic level of platform understanding is required.

This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.

To date, statistics has tended to be neatly divided into two theoretical approaches or frameworks: frequentist (or classical) and Bayesian. Scientists typically choose the statistical framework to analyse their data depending on the nature and complexity of the problem, and based on their personal views and prior training on probability and uncertainty. Although textbooks and courses should reflect and anticipate this dual reality, they rarely do so. This accessible textbook explains, discusses, and applies both the frequentist and Bayesian theoretical frameworks to fit the different types of statistical models that allow an analysis of the types of data most commonly gathered by life scientists. It presents the material in an informal, approachable, and progressive manner suitable for readers with only a basic knowledge of calculus and statistics. Statistical Modeling with R is aimed at senior undergraduate and graduate students, professional researchers, and practitioners throughout the life sciences, seeking to strengthen their understanding of quantitative methods and to apply them successfully to real world scenarios, whether in the fields of ecology, evolution, environmental studies, or computational biology.

Get insights and guidance around different challenges within the industry and what levers you can consider to lead your business transformation effortlessly enabled by RISE with SAP Key Features * Gain actionable insights into end-to-end process performance with process analytics * Scale performance and reliability to accelerate your journey to cloud and beyond * Get a good overview of the enabling tools and services which can be leveraged for the transformation Book Description If you're unsure whether adopting S/4HANA is the right move for your enterprise, then RISE with SAP to a Sustainable Enterprise is for you. This is a comprehensive guide that will help you determine your next steps and build a business case, while preparing you for all possible scenarios and helping you make informed decisions during implementation. This practical guide is packed with clear and detailed advice, including a run-through of what it takes to design the landscape with RISE with SAP. You'll gain valuable insight into precisely what services are available (such as Process Discovery, Data Migration, Fit to standard approach, what scope items on RISE with SAP should be considered) and you can make the most of RISE with the SAP-based model. You'll also get an overview of different industry-based use cases and how they can be brought to reality with the platform set up on RISE with SAP offering. By the end of this book, you will be able to build a detailed business case to determine if RISE with SAP is the right transformation engine for you. You will also get to know about an optimized landscape design on RISE with SAP that addresses the pain points for your implementation / support activities What you will learn * Understand the typical challenges organizations and CXOs are facing today with the emerging market trends * What to consider when creating a business case for RISE with SAP * Learn different types of deployment options within RISE with SAP along with other functional and non-functional services * Recommended approach when adopting S/4HANA with levers such as Process Discovery, Fit-To-Standard, Data Migration, Testing, and Automation * Learn the "Art of Possible", when dealing with SAP, Vendor ecosystem and other cloud products driven by industry use cases Who This Book Is For This book is for either the client's CXOs or solutions and enterprise architects who have been working in the SAP ecosystem and want practical and concise advice on how to get up and running toward adoption of S/4HANA leveraging RISE with SAP as the enabling engine. This book is for you also in case you are working towards creating a business case and trying to identify all possible best practices around the adoption of RISE with SAP and the associated industry use cases. Having prior experience with either SAP or a different ERP will help you get the most out of this book.

This report examines Viet Nam's tech-based startups in two sectors: agriculture and health. It assesses the challenges for creating a more enabling ecosystem to scale up startups in these sectors and makes recommendations to overcome them. Technology-based startup enterprises are an increasingly important part of the business landscape in Asia and the Pacific. By applying innovative technologies to create new products and services, they can make a significant contribution to economic development while generating social and environmental benefits. However, to survive and then thrive, tech startups require an enabling ecosystem that includes supportive government policy, adequate access to capital, skilled personnel, and quality digital infrastructure. This is the third country report in the series ""Ecosystems for Technology Startups in Asia and the Pacific.

This report assesses the current ecosystem for tech-based startups in Thailand, focusing on climate change, education, agriculture, and health. It discusses the challenges facing tech startups and provides recommendations to overcome them. Technology-based startup enterprises are an increasingly important part of the business landscape in Asia and the Pacific. By applying innovative technologies to create new products and services, they can make a significant contribution to economic development while generating social and environmental benefits. However, to survive and then thrive, tech startups require an enabling ecosystem that includes supportive government policy, access to capital, skilled personnel, quality digital infrastructure and other elements. It is the fourth country report in the series ""Ecosystems for Technology Startups in Asia and the Pacific.