"ggplot2 Essentials" takes you on a journey to mastering data visualization in R. Through this book, you will explore the full capabilities of the ggplot2 package and how it employs the principles of the grammar of graphics to create meaningful and visually appealing graphs. By reading this book, you will gain practical skills to produce stunning plots for your data analysis projects. What this Book will help me do Understand the core concepts of the grammar of graphics and how ggplot2 implements them. Learn to create a variety of plots using the ggplot2's basic and advanced functionalities. Master techniques for customizing plots, including aesthetics and graphical details. Become proficient in exporting plots in diverse formats and creating publication-ready graphs. Incorporate mapping and overlays into your plots, expanding the frontiers of ggplot2 capabilities. Author(s) Donato Teutonico is an experienced data analyst and programmer with a strong background in R and data visualization. With years of expertise, Donato specializes in creating clear, actionable tutorials for users of statistical software. His approach to teaching emphasizes practical, hands-on examples tailored to empower learners with practical plotting skills. Who is it for? This book is ideal for R programmers who want to harness the power of ggplot2 for data visualization. If you are already familiar with R and want to create more sophisticated and customizable graphics, this resource will enhance your skills. It is suited for intermediate R users aiming to discover ggplot2's features and create polished visual representations of their data. Advanced beginners passionate about data visualization will also appreciate the clear explanations and practical examples.

" If you have trouble estimating cost or schedule for your projects, you are not alone. The question is this: who wants the estimate and why? The definition of estimate is to guess. But too often, the people who want estimates want commitments. Instead of a commitment, you can apply practical and pragmatic approaches to developing estimates and then meet your commitments. You can provide your managers with the information they want and that you can live with. Learn how to use different words for your estimates and how to report an estimate that includes uncertainty. Learn who should and should not estimate. Learn how to update your estimate when you know more about your project. Regain estimation sanity. Learn practical and pragmatic ways to estimate schedule or cost for your projects."

This book provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It attempts to establish a gold standard for how a statistical analysis should proceed. The book illustrates relative belief theory using many examples and describes the strengths and weaknesses of the theory.

The First Complete Guide to Mobile App Testing and Quality Assurance: Start-to-Finish Testing Solutions for Both Android and iOS Today, mobile apps must meet rigorous standards of reliability, usability, security, and performance. However, many mobile developers have limited testing experience, and mobile platforms raise new challenges even for long-time testers. Now, Hands-On Mobile App Testing provides the solution: an end-to-end blueprint for thoroughly testing any iOS or Android mobile app. Reflecting his extensive real-life experience, Daniel Knott offers practical guidance on everything from mobile test planning to automation. He provides expert insights on mobile-centric issues, such as testing sensor inputs, battery usage, and hybrid apps, as well as advice on coping with device and platform fragmentation, and more. If you want top-quality apps as much as your users do, this guide will help you deliver them. You’ll find it invaluable–;whether you’re part of a large development team or you are the team. Learn how to Establish your optimal mobile test and launch strategy Create tests that reflect your customers, data networks, devices, and business models Choose and implement the best Android and iOS testing tools Automate testing while ensuring comprehensive coverage Master both functional and nonfunctional approaches to testing Address mobile’s rapid release cycles Test on emulators, simulators, and actual devices Test native, hybrid, and Web mobile apps Gain value from crowd and cloud testing (and understand their limitations) Test database access and local storage Drive value from testing throughout your app lifecycle Start testing wearables, connected homes/cars, and Internet of Things devices

A unique, in-depth guide to options pricing and valuing their greeks, along with a four dimensional approach towards the impact of changing market circumstances on options How to Calculate Options Prices and Their Greeks is the only book of its kind, showing you how to value options and the greeks according to the Black Scholes model but also how to do this without consulting a model. You'll build a solid understanding of options and hedging strategies as you explore the concepts of probability, volatility, and put call parity, then move into more advanced topics in combination with a four-dimensional approach of the change of the P&L of an option portfolio in relation to strike, underlying, volatility, and time to maturity. This informative guide fully explains the distribution of first and second order Greeks along the whole range wherein an option has optionality, and delves into trading strategies, including spreads, straddles, strangles, butterflies, kurtosis, vega-convexity, and more. Charts and tables illustrate how specific positions in a Greek evolve in relation to its parameters, and digital ancillaries allow you to see 3D representations using your own parameters and volumes. The Black and Scholes model is the most widely used option model, appreciated for its simplicity and ability to generate a fair value for options pricing in all kinds of markets. This book shows you the ins and outs of the model, giving you the practical understanding you need for setting up and managing an option strategy. Understand the Greeks, and how they make or break a strategy See how the Greeks change with time, volatility, and underlying Explore various trading strategies Implement options positions, and more Representations of option payoffs are too often based on a simple two-dimensional approach consisting of P&L versus underlying at expiry. This is misleading, as the Greeks can make a world of difference over the lifetime of a strategy. How to Calculate Options Prices and Their Greeks is a comprehensive, in-depth guide to a thorough and more effective understanding of options, their Greeks, and (hedging) option strategies.

The ultimate beginner's guide to SPSS and statistical analysis SPSS Statistics For Dummies is the fun and friendly guide to mastering SPSS. This book contains everything you need to know to get up and running quickly with this industry-leading software, with clear, helpful guidance on working with both the software and your data. Every chapter of this new edition has been updated with screenshots and steps that align with SPSS 23.0. You'll learn how to set up the software and organize your workflow, then delve deep into analysis to discover the power of SPSS capabilities. You'll discover the mechanics behind the calculations, perform predictive analysis, produce informative graphs, and maximize your data, even if it's been awhile since your last statistics class. SPSS is the leading statistical software for social sciences, marketing, health care, demography, government, education, data mining, and more. This powerful package gives you the tools you need to get more out of your data, and this book is your beginner-friendly guide to getting the most out of the software. Install and configure SPSS and learn the basics of how it works Master the process of getting data into SPSS and manipulating it to produce results See how to display data in dozens of different graphic formats to fit specific needs Make SPSS manufacture the numbers you want and take advantage of the many analysis options Discover ways to customize the SPSS interface and the look of your results, edit graphics and pivot tables, and program SPSS with Command Syntax Statistical analysis is crucial to so many industries, and accuracy and efficiency are crucial. SPSS offers you the capability to deliver, but you still must know how to take utmost advantage of the tools at your fingertips. SPSS Statistics For Dummies shows you how to handle data like a pro, with step-by-step instruction and expert advice.

Collecting Bayesian material scattered throughout the literature, this volume examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics. Each chapter is self-contained, gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples.

Although there are countless books on statistics, few are dedicated to the application of statistical methods to software engineering. This book fills that void. Instead of delving into overly complex statistics, it focuses on simpler solutions that are just as effective. The authors not only explain the required statistical methods, but also supply detailed examples, stories, and case studies that facilitate the understanding required to apply those methods in real-world software engineering applications.

Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ 1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso. In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.

Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.

Bridging the gap between statistics texts and SAS documentation, Elementary Statistics Using SAS is written for those who want to perform analyses to solve problems. The first section of the book explains the basics of SAS data sets and shows how to use SAS for descriptive statistics and graphs. The second section discusses fundamental statistical concepts, including normality and hypothesis testing. The remaining sections of the book show analyses for comparing two groups, comparing multiple groups, fitting regression equations, and exploring contingency tables. For each analysis, author Sandra Schlotzhauer explains assumptions, statistical approach, and SAS methods and syntax, and makes conclusions from the results. Statistical methods covered include two-sample t-tests, paired-difference t-tests, analysis of variance, multiple comparison techniques, regression, regression diagnostics, and chi-square tests. Elementary Statistics Using SAS is a thoroughly revised and updated edition of Ramon Littell and Sandra Schlotzhauer's SAS System for Elementary Statistical Analysis. This book is part of the SAS Press program.

Features basic statistical concepts as a tool for thinking critically, wading through large quantities of information, and answering practical, everyday questions Written in an engaging and inviting manner, Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know presents the more subjective side of statistics—the art of data analytics. Each chapter explores a different question using fun, common sense examples that illustrate the concepts, methods, and applications of statistical techniques. Without going into the specifics of theorems, propositions, or formulas, the book effectively demonstrates statistics as a useful problem-solving tool. In addition, the author demonstrates how statistics is a tool for thinking critically, wading through large volumes of information, and answering life's important questions. Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know also features: Plentiful examples throughout aimed to strengthen readers' understanding of the statistical concepts and methods A step-by-step approach to elementary statistical topics such as sampling, hypothesis tests, outlier detection, normality tests, robust statistics, and multiple regression A case study in each chapter that illustrates the use of the presented techniques Highlights of well-known shortcomings that can lead to false conclusions An introduction to advanced techniques such as validation and bootstrapping Featuring examples that are engaging and non-application specific, the book appeals to a broad audience of students and professionals alike, specifically students of undergraduate statistics, managers, medical professionals, and anyone who has to make decisions based on raw data or compiled results.

In "Data Visualization with D3 and AngularJS," you'll discover how to create dynamic, data-driven visualizations with the power of D3.js integrated seamlessly into AngularJS apps. This book offers a hands-on approach, demonstrating step-by-step how to leverage the strengths of these technologies to build interactive dashboards and visual components. What this Book will help me do Build and integrate interactive dashboards using D3.js and AngularJS. Design varied types of charts, including scatter plots, bar graphs, and area charts. Understand how to load, parse, and preprocess external data for visualizations. Develop modular and reusable visualization components in AngularJS. Create custom animations and interactions for user engagement with data visualizations. Author(s) With years of experience in front-end development and data visualization, the authors None Hanchett and None Körner bring expert insight and clarity to these topics. Their instructional approach focuses on practical, real-world applications, aiming to empower readers to achieve professional results through clear explanations and well-structured examples. Who is it for? This book is tailored for web developers familiar with AngularJS who are eager to incorporate advanced visualizations into their applications. Whether you're looking to build professional dashboards or simply explore the capabilities of D3.js, this book provides the knowledge you need. Ideal for those aiming to gain hands-on experience and enhance their development skill set.

Learning Tableau is your guide to mastering Tableau 9.0 for building impactful data visualizations and creating interactive, insightful dashboards. Whether you're beginning your data visualization journey or seek to refine your skills, this book provides a comprehensive approach to unlocking the potential of your data. What this Book will help me do Understand how to create basic and advanced visualizations for effective data representation. Learn techniques to enhance data analysis through custom calculations and interactive features. Gain skills to integrate and analyze data from multiple sources using Tableau's blending and joining features. Master the art of designing and formatting visually appealing dashboards to tell compelling data stories. Explore advanced Tableau functionalities like LOD calculations and sheet swapping to improve analytical insights. Author(s) Joshua N. Milligan is a seasoned data professional with a wealth of experience in Tableau. As a Tableau Zen Master, he combines his practical expertise and in-depth knowledge to craft a beginner-friendly guide for professionals looking to grasp Tableau's features effectively. His approachable and engaging writing style makes complex concepts accessible. Who is it for? This book is ideal for professionals and enthusiasts aiming to develop their skills in data visualization and Tableau. It's suitable for individuals with basic knowledge of data or databases, but no prior Tableau experience is necessary. Whether you're a data analyst, business professional, or IT specialist, this book will help you communicate data insights clearly. Readers will achieve a comprehensive understanding of Tableau 9.0's capabilities to create valuable outcomes.

In Statistical Programming in SAS, author A. John Bailer integrates SAS tools with interesting statistical applications and uses SAS 9.2 as a platform to introduce programming ideas for statistical analysis, data management, and data display and simulation. Written using a reader-friendly and narrative style, the book includes extensive examples and case studies to present a well-structured introduction to programming issues.

This book is designed for engineering students studying for the core paper on probability and statistics. The topics have been dealt in a coherent manner, supported by illustrations for better compre¬hension. Each chapter is replete with examples and exercises. The book also has numerous Multiple Choice Questions at the end of each chapter, thus providing the student with an abundant repository of exam specific problems.

This book guides you through an enjoyable journey, step by step, into the future. A team of fictional characters is introduced to share their learning and working experiences with the readers. In the beginning of the book, you will take the first step by learning the most basic models for one-period forecasts based on past performance of a market. You will also learn how to evaluate your newly built models. Next, you will progress further into intermediate-level models, including multi-period forecasts based on past performance of a market or based on an external factor. It also introduces interval forecasting, which allows you to obtain a range of forecast values instead of a single value in the future. In the second half, you will familiarize yourself with advanced models that provide multi-period forecasts based on multiple internal or external factors. Toward the end, you will learn several applied models in business and economics that will facilitate you with practical applications related to real life situations. The  last chapter summarizes all models introduced in this book and provides a table of references for finding the most important concepts, tables, and figures in the book so that you can recall every step of your adventure.

This book shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years of research in this area, the author presents a thorough overview of the statistical theory, properties, and applications of PIMs. He covers a range of PIMs, including models for misclassified data and models involving instrumental variables. He also includes real data applications of PIMs that have recently appeared in the literature.

Risk analysis has become critical to modern financial planning Financial Forecasting, Analysis and Modelling provides a complete framework of long-term financial forecasts in a practical and accessible way, helping finance professionals include uncertainty in their planning and budgeting process. With thorough coverage of financial statement simulation models and clear, concise implementation instruction, this book guides readers step-by-step through the entire projection plan development process. Readers learn the tools, techniques, and special considerations that increase accuracy and smooth the workflow, and develop a more robust analysis process that improves financial strategy. The companion website provides a complete operational model that can be customised to develop financial projections or a range of other key financial measures, giving readers an immediately-applicable tool to facilitate effective decision-making. In the aftermath of the recent financial crisis, the need for experienced financial modelling professionals has steadily increased as organisations rush to adjust to economic volatility and uncertainty. This book provides the deeper level of understanding needed to develop stronger financial planning, with techniques tailored to real-life situations. Develop long-term projection plans using Excel Use appropriate models to develop a more proactive strategy Apply risk and uncertainty projections more accurately Master the Excel Scenario Manager, Sensitivity Analysis, Monte Carlo Simulation, and more Risk plays a larger role in financial planning than ever before, and possible outcomes must be measured before decisions are made. Uncertainty has become a critical component in financial planning, and accuracy demands it be used appropriately. With special focus on uncertainty in modelling and planning, Financial Forecasting, Analysis and Modelling is a comprehensive guide to the mechanics of modern finance.

This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains analytical techniques such as modeling, data mining, and multivariate analysis for social big data. This book is different from other similar books in that presents the overall picture of social big data from fundamental concepts to applications while standing on academic bases.