Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. With this book you will review contemporary MATLAB coding including the latest MATLAB language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. Features now covered include the new graph and digraph classes for charts and networks; interactive documents that combine text, code, and output; a new development environment for building apps; locally defined functions in scripts; automatic expansion of dimensions; tall arrays for big data; the new string type; new functions to encode/decode JSON; handling non-English languages; the new class architecture; the Mocking framework; an engine API for Java; the cloud-based MATLAB desktop; the memoize function; and heatmap charts. MATLAB Recipes: A Problem-Solution Approach, Second Edition provides practical, hands-on code snippets and guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm. What You Will Learn Get up to date with the latest MATLAB up to and including MATLAB 2020b Code in MATLAB Write applications in MATLAB Build your own toolbox of MATLAB code to increase your efficiency and effectiveness Who This Book Is For Engineers, data scientists, and students wanting a book rich in examples using MATLAB.

Enhance your data science programming and analysis with the Wolfram programming language and Mathematica, an applied mathematical tools suite. The book will introduce you to the Wolfram programming language and its syntax, as well as the structure of Mathematica and its advantages and disadvantages. You’ll see how to use the Wolfram language for data science from a theoretical and practical perspective. Learning this language makes your data science code better because it is very intuitive and comes with pre-existing functions that can provide a welcoming experience for those who use other programming languages. You’ll cover how to use Mathematica where data management and mathematical computations are needed. Along the way you’ll appreciate how Mathematica provides a complete integrated platform: it has a mixed syntax as a result of its symbolic and numerical calculations allowing it to carry out various processes without superfluous lines of code. You’ll learn to use its notebooks as a standard format, which also serves to create detailed reports of the processes carried out. What You Will Learn Use Mathematica to explore data and describe the concepts using Wolfram language commands Create datasets, work with data frames, and create tables Import, export, analyze, and visualize data Work with the Wolfram data repository Build reports on the analysis Use Mathematica for machine learning, with different algorithms, including linear, multiple, and logistic regression; decision trees; and data clustering Who This Book Is For Data scientists new to using Wolfram and Mathematica as a language/tool to program in. Programmers should have some prior programming experience, but can be new to the Wolfram language.

Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.

Microsoft Power Apps Cookbook provides a comprehensive set of step-by-step recipes for creating efficient and customized business applications using Power Apps' low-code capabilities. Through this book, you'll gain practical skills to build apps that address real-world business needs with increased agility and speed. What this Book will help me do Create and integrate canvas apps effectively, enhancing collaborative solutions. Leverage Microsoft Dataverse to design robust, model-driven app solutions. Utilize automated workflows through Power Automate, including business process automations and RPAs. Incorporate advanced components such as AI Builder capabilities into your designed apps. Develop web experiences for users with Microsoft Power Pages, extending the reach beyond the organization. Author(s) Eickhel Mendoza is a seasoned expert in Microsoft Power Platform who has been involved in numerous enterprise projects utilizing Power Apps and related technologies. With extensive experience in low-code solutions, Eickhel is passionate about simplifying complex business processes and empowering readers to achieve business agility through practical application. He focuses on clear guidance and real-world applicability in this hands-on resource to enhance your learning experience. Who is it for? This book is suited for both citizen developers and business users who want to create tailored apps meeting specific organizational needs, and for traditional app developers interested in maximizing productivity with low-code development tools. Beginners in Power Apps with basic familiarity will find actionable knowledge to overcome challenges in real-world cases. Experienced professionals will appreciate the advanced techniques shared.

The Data Mirage: Why Companies Fail to Actually Use Their Data is a business book for executives and leaders who want to unlock more insights from their data and make better decisions. The importance of data doesn’t need an introduction or a fancy pitch deck. Data plays a critical role in helping companies to better understand their users, beat out their competitors, and breakthrough their growth targets. However, despite significant investments in their data, most organizations struggle to get much value from it. According to Forrester, only 38% of senior executives and decision-makers “have a high level of confidence in their customer insights and only 33% trust the analytics they generate from their business operations.” This reflects the real world that I have experienced. In this book, I will help readers formulate an analytics strategy that works in the real world, show them how to think about KPIs and help them tackle the problems they are bound to come across as they try to use data to make better decisions.

Handbook of Analytical Quality by Design addresses the steps involved in analytical method development and validation in an effort to avoid quality crises in later stages. The AQbD approach significantly enhances method performance and robustness which are crucial during inter-laboratory studies and also affect the analytical lifecycle of the developed method. Sections cover sample preparation problems and the usefulness of the QbD concept involving Quality Risk Management (QRM), Design of Experiments (DoE) and Multivariate (MVT) Statistical Approaches to solve by optimizing the developed method, along with validation for different techniques like HPLC, UPLC, UFLC, LC-MS and electrophoresis. This will be an ideal resource for graduate students and professionals working in the pharmaceutical industry, analytical chemistry, regulatory agencies, and those in related academic fields. Concise language for easy understanding of the novel and holistic concept Covers key aspects of analytical development and validation Provides a robust, flexible, operable range for an analytical method with greater excellence and regulatory compliance

Use Predictive Analytics to Uncover Hidden Patterns and Correlations and Improve Decision-Making Using predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data and leverage these insights to improve many key business decisions. In this thoroughly updated guide, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for both business professionals and students. Delen provides a holistic approach covering key data mining processes and methods, relevant data management techniques, tools and metrics, advanced text and web mining, big data integration, and much more. Balancing theory and practice, Delen presents intuitive conceptual illustrations, realistic example problems, and real-world case studiesincluding lessons from failed projects. It is all designed to help you gain a practical understanding you can apply for profit. * Leverage knowledge extracted via data mining to make smarter decisions * Use standardized processes and workflows to make more trustworthy predictions * Predict discrete outcomes (via classification), numeric values (via regression), and changes over time (via time-series forecasting) * Understand predictive algorithms drawn from traditional statistics and advanced machine learning * Discover cutting-edge techniques, and explore advanced applications ranging from sentiment analysis to fraud detection .

Reduce the cost and time of cleaning, managing, and preparing research data while also improving data quality! Have you ever wished there was an easy way to reduce your workload and improve the quality of your data? The Data Detective’s Toolkit: Cutting-Edge Techniques and SAS Macros to Clean, Prepare, and Manage Data will help you automate many of the labor-intensive tasks needed to turn raw data into high-quality, analysis-ready data. You will find the right tools and techniques in this book to reduce the amount of time needed to clean, edit, validate, and document your data. These tools include SAS macros as well as ingenious ways of using SAS procedures and functions. The innovative logic built into the book’s macro programs enables you to monitor the quality of your data using information from the formats and labels created for the variables in your data set. The book explains how to harmonize data sets that need to be combined and automate data cleaning tasks to detect errors in data including out-of-range values, inconsistent flow through skip paths, missing data, no variation in values for a variable, and duplicates. By the end of this book, you will be able to automatically produce codebooks, crosswalks, and data catalogs.

This book presents key concepts related to quantitative analysis in business. It is targeted at business students (both undergraduate and graduate) taking an introductory core course. Business analytics has grown to be a key topic in business curricula, and there is a need for stronger quantitative skills and understanding of fundamental concepts. This second edition adds material on Tableau, a very useful software for business analytics. This supplements the tools from Excel covered in the first edition, to include Data Analysis Toolpak and SOLVER.

Business Analytics is now a part and parcel of MBA curriculum of most institutions, as business organizations expect the new managers to have a basic knowledge of Analytics. There is also an emerging career opportunity for management graduates with deeper knowledge of Analytics. These professionals would be in Analytics roles, where business knowledge is critical. In this respect, this book will be a suitable textbook for students at postgraduate level. Beyond this, it will be a refresher material for working professionals.

Features –

1. The book is structured to mimic stages of a typical Analytic process.
2. This book starts with understanding business problem, data cleaning, exploratory data analysis, model building, model implementation and evaluation.
3. An in-depth explanation is provided on the concept of ‘Modelling’
4. The book contain many interesting caselet and box items discussing on interesting facts and figures relevant to the current industrial scenarios.
5. Resource material for this book includes, Instructor PPT, MCQ, Data sets and Codes for practise and set of research questions to take up mini projects.

Google Data Studio is becoming a go-to tool in the analytics community. All business roles across the industry benefit from foundational knowledge of this now-essential technology, and Google Data Studio for Beginners is here to provide it. Release your locked-up data and turn it into beautiful, actionable, and shareable reports that can be consumed by experts and novices alike. Authors Grant Kemp and Gerry White begin by walking you through the basics, such how to create simple dashboards and interactive visualizations. As you progress through Google Data Studio for Beginners, you will build up the knowledge necessary to blend multiple data sources and create comprehensive marketing dashboards. Some intermediate features such as calculated fields, cleaning up data, and data blending to build powerhouse reports are featured as well. Presenting your data in client-ready, digestible forms is a key factor that many find to be a roadblock, and this book will help strengthen this essential skill in your organization. Centralizing the power from sources such as Google Analytics, online surveys, and a multitude of other popular data management tools puts you as a business leader and analyzer ahead of the rest. Your team as a whole will benefit from Google Data Studio for Beginners, because by using these tools, teams can collaboratively work on data to build their understanding and turn their data into action. Data Studio is quickly solidifying itself as the industry standard, and you don’t want to miss this essential guide for excelling in it. What You Will Learn Combine various data sources to create great looking and actionable visualizations Reuse and modify other dashboards that have been created by industry pros Use intermediate features such as calculated fields and data blending to build powerhouse reports Who This Book Is For Users looking to learn Google Analytics, SEO professionals, digital marketers, and other business professionals who want to mine their data into an actionable dashboard.

Modern power system analysis with MATLAB applications aims to cater to the curriculum requirements of the undergraduate students and faculties of electrical and Electronics.Engineering for the course on power system analysis. Spread across ten chapters, The book aims to provide an in-depth understanding of the necessary theories. Special care has been taken to explain the development of mathematical models required for the power system analysis problems. Wherever required, MATLAB programs and the corresponding solutions are presented to motivate the students to use the MATLAB programs for small, medium and large size power system problems

Prepare for Microsoft Exam PL-900: Demonstrate your real-world knowledge of the fundamentals of Microsoft Power Platform, including its business value, core components, and the capabilities and advantages of Power BI, Power Apps, Power Automate, and Power Virtual Agents. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Power Platform Fundamentals level. Focus on the expertise measured by these objectives: Describe the business value of Power Platform Identify the Core Components of Power Platform Demonstrate the capabilities of Power BI Demonstrate the capabilities of Power Apps Demonstrate the capabilities of Power Automate Demonstrate the capabilities of Power Virtual Agents This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are a business user, functional consultant, or other professional who wants to improve productivity by automating business processes, analyzing data, creating simple app experiences, or developing business enhancements to Microsoft cloud solutions. About the Exam Exam PL-900 focuses on knowledge needed to describe the value of Power Platform services and of extending solutions; describe Power Platform administration and security; describe Common Data Service, Connectors, and AI Builder; identify common Power BI components; connect to and consume data; build basic dashboards with Power BI; identify common Power Apps components; build basic canvas and model-driven apps; describe Power Apps portals; identify common Power Automate components; build basic flows; describe Power Virtual Agents capabilities; and build and publish basic chatbots. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Power Platform Fundamentals certification, demonstrating your understanding of Power Platforms core capabilitiesfrom business value and core product capabilities to building simple apps, connecting data sources, automating basic business processes, creating dashboards, and creating chatbots. With this certification, you can move on to earn specialist certifications covering more advanced aspects of Power Apps and Power BI, including Microsoft Certified: Power Platform App Maker Associate and Power Platform Data Analyst Associate. See full details at: microsoft.com/learn

Prepare for Microsoft Exam PL-900: Demonstrate your real-world knowledge of the fundamentals of Microsoft Power Platform, including its business value, core components, and the capabilities and advantages of Power BI, Power Apps, Power Automate, and Power Virtual Agents. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Power Platform Fundamentals level. Focus on the expertise measured by these objectives: Describe the business value of Power Platform Identify the Core Components of Power Platform Demonstrate the capabilities of Power BI Demonstrate the capabilities of Power Apps Demonstrate the capabilities of Power Automate Demonstrate the capabilities of Power Virtual Agents This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are a business user, functional consultant, or other professional who wants to improve productivity by automating business processes, analyzing data, creating simple app experiences, or developing business enhancements to Microsoft cloud solutions. About the Exam Exam PL-900 focuses on knowledge needed to describe the value of Power Platform services and of extending solutions; describe Power Platform administration and security; describe Common Data Service, Connectors, and AI Builder; identify common Power BI components; connect to and consume data; build basic dashboards with Power BI; identify common Power Apps components; build basic canvas and model-driven apps; describe Power Apps portals; identify common Power Automate components; build basic flows; describe Power Virtual Agents capabilities; and build and publish basic chatbots. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Power Platform Fundamentals certification, demonstrating your understanding of Power Platforms core capabilitiesfrom business value and core product capabilities to building simple apps, connecting data sources, automating basic business processes, creating dashboards, and creating chatbots. With this certification, you can move on to earn specialist certifications covering more advanced aspects of Power Apps and Power BI, including Microsoft Certified: Power Platform App Maker Associate and Power Platform Data Analyst Associate. See full details at: microsoft.com/learn

Discover new theoretical connections between stochastic phenomena and the structure of natural language with this powerful volume! Information Theory Meets Power Laws: Stochastic Processes and Language Models presents readers with a novel subtype of a probabilistic approach to language, which is based on statistical laws of texts and their analysis by means of information theory. The distinguished author insightfully and rigorously examines the linguistic and mathematical subject matter while eschewing needlessly abstract and superfluous constructions. The book begins with a less formal treatment of its subjects in the first chapter, introducing its concepts to readers without mathematical training and allowing those unfamiliar with linguistics to learn the book’s motivations. Despite its inherent complexity, Information Theory Meets Power Laws: Stochastic Processes and Language Models is a surprisingly approachable treatment of idealized mathematical models of human language. The author succeeds in developing some of the theory underlying fundamental stochastic and semantic phenomena, like strong nonergodicity, in a way that has not previously been seriously attempted. In doing so, he covers topics including: Zipf’s and Herdan’s laws for natural language Power laws for information, repetitions, and correlations Markov, finite-state,and Santa Fe processes Bayesian and frequentist interpretations of probability Ergodic decomposition, Kolmogorov complexity, and universal coding Theorems about facts and words Information measures for fields Rényi entropies, recurrence times, and subword complexity Asymptotically mean stationary processes Written primarily for mathematics graduate students and professionals interested in information theory or discrete stochastic processes, Information Theory Meets Power Laws: Stochastic Processes and Language Models also belongs on the bookshelves of doctoral students and researchers in artificial intelligence, computational and quantitative linguistics as well as physics of complex systems.

Gain a comprehensive understanding of Microsoft Power Platform as you prepare for the PL-200 Functional Consultant Exam. Dive into practical, hands-on guidance to customize and configure the platform effectively. What this Book will help me do Master the art of creating and configuring model-driven and canvas Power Apps. Learn to develop automated processes with Power Automate and manage workflows. Understand the setup and role of Dataverse for robust data handling within Power Platform. Integrate Power Platform tools with Microsoft 365 and Teams effectively. Prepare confidently for the PL-200 certification with mock exams and detailed insights. Author(s) None Sharp is an experienced consultant specializing in Microsoft technologies, including the Power Platform. With years of expertise helping organizations optimize their workflows, None brings practical insights and a structured approach to learning. This book reflects their commitment to educating aspiring consultants and Microsoft technology users. Who is it for? This book is ideal for functional consultants and business analysts in the technology space seeking to leverage Microsoft Power Platform. It's particularly suited for professionals preparing for the PL-200 certification. A foundation in Power Platform concepts will help readers make the most of this resource.

Master the fundamentals of regression without learning calculus with this one-stop resource The newly and thoroughly revised 3rd Edition of Applied Regression Modeling delivers a concise but comprehensive treatment of the application of statistical regression analysis for those with little or no background in calculus. Accomplished instructor and author Dr. Iain Pardoe has reworked many of the more challenging topics, included learning outcomes and additional end-of-chapter exercises, and added coverage of several brand-new topics including multiple linear regression using matrices. The methods described in the text are clearly illustrated with multi-format datasets available on the book's supplementary website. In addition to a fulsome explanation of foundational regression techniques, the book introduces modeling extensions that illustrate advanced regression strategies, including model building, logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series forecasting. Illustrations, graphs, and computer software output appear throughout the book to assist readers in understanding and retaining the more complex content. Applied Regression Modeling covers a wide variety of topics, like: Simple linear regression models, including the least squares criterion, how to evaluate model fit, and estimation/prediction Multiple linear regression, including testing regression parameters, checking model assumptions graphically, and testing model assumptions numerically Regression model building, including predictor and response variable transformations, qualitative predictors, and regression pitfalls Three fully described case studies, including one each on home prices, vehicle fuel efficiency, and pharmaceutical patches Perfect for students of any undergraduate statistics course in which regression analysis is a main focus, Applied Regression Modeling also belongs on the bookshelves of non-statistics graduate students, including MBAs, and for students of vocational, professional, and applied courses like data science and machine learning.

  This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.

The book will discuss the statistical methods involved, covers the development of academic writing skills for a higher impact, teaches learning theories, and uses a structured and holistic approach for educational research proposal development.

Create industry-compliant graphs with this practical guide for professionals Analysis of clinical trial results is easier when the data is presented in a visual form. However, clinical graphs must conform to specific guidelines in order to satisfy regulatory agency requirements. If you are a programmer working in the health care and life sciences industry and you want to create straightforward, visually appealing graphs using SAS, then this book is designed specifically for you. Written by two experienced practitioners, the book explains why certain graphs are requested, gives the necessary code to create the graphs, and shows you how to create graphs from ADaM data sets modeled on real-world CDISC pilot study data. SAS Graphics for Clinical Trials by Example demonstrates step-by-step how to create both simple and complex graphs using Graph Template Language (GTL) and statistical graphics procedures, including the SGPLOT and SGPANEL procedures. You will learn how to generate commonly used plots such as Kaplan-Meier plots and multi-cell survival plots as well as special purpose graphs such as Venn diagrams and interactive graphs. Because your graph is only as good as the aesthetic appearance of the output, you will learn how to create a custom style, change attributes, and set output options. Whether you are just learning how to produce graphs or have been working with graphs for a while, this book is a must-have resource to solve even the most challenging clinical graph problems.