The easy way to get started coding and analyzing data in the R programming language Statistical Analysis with R Essentials For Dummies is your reference to all the core concepts about R—the widely used, open-source programming language and data analysis tool. This no-nonsense book gets right to the point, eliminating review material, wordy explanations, and fluff. Understand all you need to know about the foundations of R, swiftly and clearly. Perfect for a brush-up on the basics or as an everyday desk reference on the job, this is the reliable little book you can always turn to for answers. Get a quick and thorough intro to the basic concepts of coding for data analysis in R Review what you've already learned or pick up essential new skills Perform statistical analysis for school, business, and beyond with R programming Keep this concise reference book handy for jogging your memory as you work This book is to the point, focusing on the key topics readers need to know about this popular programming language. Great for supplementing classroom learning, reviewing for a certification, or staying knowledgeable on the job.

Offering a pathway to vibrant organizations, this book integrates systems thinking, critical thinking, and design thinking, and provides the tools needed to proactively apply them in the social systems where we live and work.

Unlock the Power of Data: Transform Your Marketing Strategies with Data Science In the digital age, understanding the symbiosis between marketing and data science is not just an advantage; it's a necessity. In Mastering Marketing Data Science: A Comprehensive Guide for Today's Marketers, Dr. Iain Brown, a leading expert in data science and marketing analytics, offers a comprehensive journey through the cutting-edge methodologies and applications that are defining the future of marketing. This book bridges the gap between theoretical data science concepts and their practical applications in marketing, providing readers with the tools and insights needed to elevate their strategies in a data-driven world. Whether you're a master's student, a marketing professional, or a data scientist keen on applying your skills in a marketing context, this guide will empower you with a deep understanding of marketing data science principles and the competence to apply these principles effectively. Comprehensive Coverage: From data collection to predictive analytics, NLP, and beyond, explore every facet of marketing data science. Practical Applications: Engage with real-world examples, hands-on exercises in both Python & SAS, and actionable insights to apply in your marketing campaigns. Expert Guidance: Benefit from Dr. Iain Brown's decade of experience as he shares cutting-edge techniques and ethical considerations in marketing data science. Future-Ready Skills: Learn about the latest advancements, including generative AI, to stay ahead in the rapidly evolving marketing landscape. Accessible Learning: Tailored for both beginners and seasoned professionals, this book ensures a smooth learning curve with a clear, engaging narrative. Mastering Marketing Data Science is designed as a comprehensive how-to guide, weaving together theory and practice to offer a dynamic, workbook-style learning experience. Dr. Brown's voice and expertise guide you through the complexities of marketing data science, making sophisticated concepts accessible and actionable.

Business Statistics, 3rd Edition 3rd Edition

Business Statistics: An Applied Orientation provides with a conceptual framework of business, develops skills in applying concepts into decision situations, and helps understand the nitty-gritty of business statistics. This book will also be useful to professionals who would like to acquire basic knowledge of business statistics that would help them analyze and interpret data.

Business Statistics offers readers a foundation in core statistical concepts using a perfect blend of theory and practical application. This book presents business statistics as value added tools in the process of converting data into useful information.

Valuable resource for researchers and postgraduate students from statistics, biostatistics, and other fields. It could be used as a textbook for a course on model-based clustering methods, and as a supplementary text for courses on data mining, semiparametric modeling, and high-dimensional data analysis.

Start your journey with SAS. Have you just accepted a new job as a data analyst and need to learn SAS fast? Or perhaps you want to make a career change into programming and you’re not sure where to begin. The Simple Guide to SAS: From Null to Novice is the perfect book to get you started. Written for individuals with no prior programming experience, this book teaches the basics of learning SAS using hands-on examples and step-by-step explanations in a short, easy-to-understand guide. Topics covered in this book include: DATA and PROC Steps DATA Step Processing Setting Up SAS Libraries Importing and Exporting Data Viewing and Summarizing Data Sorting and De-duplicating Data Filtering Data and Conditional Logic SAS Functions Formatting Variables Combining and Aggregating Data The Simple Guide to SAS provides solutions to common business problems, identifies pitfalls to avoid, and includes sample code with data for readers to practice their knowledge.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science. Examples are provided in Python, drawn from popular packages such as NumPy and pandas. If you want to write better data science code, this guide covers the essential topics that are often missing from introductory data science or coding classes, including how to: Understand data structures and object-oriented programming Clearly and skillfully document your code Package and share your code Integrate data science code with a larger code base Learn how to write APIs Create secure code Apply best practices to common tasks such as testing, error handling, and logging Work more effectively with software engineers Write more efficient, maintainable, and robust code in Python Put your data science projects into production And more

Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sources Organize and analyze data Use data to tell a story with Tableau Expand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.

The Complete Power BI Interview Guide is your companion to mastering Power BI roles and acing data analyst interviews. With hands-on skills, expert tips, and targeted preparation strategies, this resource equips you to excel in interviews and certifications while navigating the competitive job market. What this Book will help me do Create a powerful professional brand to optimize your resume and online presence. Master essential Power BI skills including data modeling, DAX programming, and visualization. Prepare effectively for interviews with industry-relevant questions, answers, and insights. Gain an edge in the market by understanding hiring procedures and negotiation tactics. Develop comprehensive analytics solutions exemplified with real-world case studies. Author(s) Sandielly Ortega Polanco, Gogula Aryalingam, and Abu Bakar Nisar Alvi bring years of collective experience in data analytics, Power BI, and career mentorship. Their insights are drawn from extensive professional practice and their passion for empowering future data analysts. Together, they provide an approachable and practical guide to securing roles in the competitive landscape of data analytics. Who is it for? This book is ideal for aspiring data analysts, business intelligence developers, or those shifting into Power BI roles who wish to enhance their knowledge and refine their strategies for interview success. It speaks to both newcomers to the field and seasoned professionals aiming to elevate their expertise.

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate. Jen Stirrup, CEO of AI and BI leadership consultancy Data Relish, and Thomas Weinandy, research economist at Upside, show you how to use data already available to your organization. Springboarding from the skills that you already possess, this book adds AI to your organization's technical capability and expertise with Microsoft Power BI. By using your conceptual knowledge of BI, you'll learn how to choose the right model for your AI work and identify its value and validity. Use Power BI to build a good data model for AI Demystify the AI terminology that you need to know Identify AI project roles, responsibilities, and teams for AI Use AI models, including supervised machine learning techniques Develop and train models in Azure ML for consumption in Power BI Improve your business AI maturity level with Power BI Use the AI feedback loop to help you get started with the next project

In "Extending Power BI with Python and R," you'll learn how to enhance your Power BI reports and analyses by leveraging the advanced analytical capabilities of Python and R. From working with large datasets to creating sophisticated visuals, this book provides practical instructions on powerful techniques that unlock new possibilities in Power BI. What this Book will help me do Configure and optimize Python and R integration in Power BI for enhanced performance. Implement advanced data transformation techniques to overcome Power BI limitations. Develop advanced visualizations using the Grammar of Graphics in Python and R. Analyze data leveraging powerful Python and R algorithms, including machine learning models. Secure your Power BI data with anonymization and pseudonymization techniques. Author(s) None Zavarella is a data analytics expert with years of practical experience in business intelligence and data analytics. With a passion for enhancing data tools with programming languages like Python and R, they bring practical knowledge and technical acumen to this comprehensive resource. They aim to make complex concepts approachable to their readers. Who is it for? This book is aimed at professionals such as business analysts, business intelligence specialists, and data scientists who leverage Power BI for their data solutions. Readers should have a working knowledge of Power BI basics and a desire to extend its capabilities. A familiarity with Python and R programming basics is also beneficial for following the advanced techniques presented.

Master the art and science of analytics engineering with 'Fundamentals of Analytics Engineering.' This book takes you on a comprehensive journey from understanding foundational concepts to implementing end-to-end analytics solutions. You'll gain not just theoretical knowledge but practical expertise in building scalable, robust data platforms to meet organizational needs. What this Book will help me do Design and implement effective data pipelines leveraging modern tools like Airbyte, BigQuery, and dbt. Adopt best practices for data modeling and schema design to enhance system performance and develop clearer data structures. Learn advanced techniques for ensuring data quality, governance, and observability in your data solutions. Master collaborative coding practices, including version control with Git and strategies for maintaining well-documented codebases. Automate and manage data workflows efficiently using CI/CD pipelines and workflow orchestrators. Author(s) Dumky De Wilde, alongside six co-authors-experienced professionals from various facets of the analytics field-delivers a cohesive exploration of analytics engineering. The authors blend their expertise in software development, data analysis, and engineering to offer actionable advice and insights. Their approachable ethos makes complex concepts understandable, promoting educational learning. Who is it for? This book is a perfect fit for data analysts and engineers curious about transitioning into analytics engineering. Aspiring professionals as well as seasoned analytics engineers looking to deepen their understanding of modern practices will find guidance. It's tailored for individuals aiming to boost their career trajectory in data engineering roles, addressing fundamental to advanced topics.

Dive into the comprehensive world of data transformation with "The Definitive Guide to Power Query (M)". This book empowers you with the knowledge and skills necessary to effectively utilize Power Query for complex data transformation tasks. You will develop expertise in practical techniques, advanced M language concepts, and optimization strategies. What this Book will help me do Understand the fundamentals of Power Query and its functionalities. Learn to perform complex data transformations using various Power Query functions. Gain insight into advanced M language structures such as custom functions and nested expressions. Develop skills in error handling and debugging to streamline your data processes. Master performance optimization techniques for efficient data handling with Power Query. Author(s) Gregory Deckler, Rick de Groot, and Melissa de Korte are seasoned professionals in business intelligence and data analytics. With years of experience using Power Query, they bring a wealth of knowledge and practical insight into tackling real-world data problems. Their combined expertise ensures a clear and immersive learning experience for readers, guiding them through fundamental to advanced topics. Who is it for? This book is ideal for business analysts, data professionals, and power users who wish to advance their data transformation capabilities. If you're someone with foundational experience in Power Query looking to become proficient or an industry professional aiming to optimize workflows, this book is tailored to suit your goals.

This fully updated second edition is an essential introduction to inferential statistics. It is the first introductory statistics text to use an estimation approach with meta-analysis from the start and also to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research.

This book highlights how optimized big data applications can be used for patient monitoring and clinical diagnosis. In fact, IoT-based applications are data-driven and mostly employ modern optimization techniques. The book also explores challenges, opportunities, and future research directions, discussing the stages of data collection and pre-processing, as well as the associated challenges and issues in data handling and setup.

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular problem and follow the steps in the solution. This book has something for everyone interested in machine learning. It also has material that will allow those with an interest in other technology areas to see how machine learning and MATLAB can help them solve problems in their areas of expertise. The chapter on data representation and MATLAB graphics includes new data types and additional graphics. Chapters on fuzzy logic, simple neural nets, and autonomous driving have new examples added. And there is a new chapter on spacecraft attitude determination using neural nets. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow you to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What You Will Learn Write code for machine learning, adaptive control, and estimation using MATLAB Use MATLAB graphics and visualization tools for machine learning Become familiar with neural nets Build expert systems Understand adaptive control Gain knowledge of Kalman Filters Who This Book Is For Software engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists.

Microsoft 365 Excel introduces enhanced features that transform how business dashboards are built and maintained. This book guides you through creating dynamic, interactive dashboards that leverage these modern capabilities. From understanding the essential principles of effective dashboard design to mastering the latest tools like Power Query and dynamic array functions, you'll make the most of Excel's full potential. What this Book will help me do Understand the purpose and advantages of effective dashboards in business analytics. Use advanced Excel functions and tools such as Power Query and dynamic arrays to handle complex data workflows. Design visually engaging dashboards using charts and data visualizations that communicate key insights. Optimize dashboards for automation and real-time data updates, saving time and effort. Apply best practices and techniques for creating professional-grade Excel dashboards. Author(s) Michael Olafusi is a skilled data analyst and expert in Microsoft Excel, with years of experience leveraging Excel for business intelligence and analytics solutions. He enjoys teaching Excel users how to elevate their skills to create functional and visually impactful tools. Michael's approach combines clarity and practical advice, helping readers build proficiency and confidence. Who is it for? This book is perfect for Excel users who want to create professional dashboards for business decision support. It's especially useful for data analysts, financial analysts, business analysts, and those in similar roles. It requires a basic familiarity with Excel's interface and is ideal for those seeking to enhance their data presentation skills and automate repetitive reporting tasks.

"Cracking the Data Science Interview" is your ultimate resource for preparing for roles in the competitive field of data science. With this book, you'll explore essential topics such as Python, SQL, statistics, and machine learning, as well as learn practical skills for building portfolios and acing interviews. Follow its guidance and you'll be equipped to stand out in any data science interview. What this Book will help me do Confidently explain complex statistical and machine learning concepts. Develop models and deploy them while ensuring version control and efficiency. Learn and apply scripting skills in shell and Bash for productivity. Master Git workflows to handle collaborative coding in projects. Perfectly tailor portfolios and resumes to land data science opportunities. Author(s) Leondra R. Gonzalez, with years of data science and mentorship experience, co-authors this book with None Stubberfield, a seasoned expert in technology and machine learning. Together, they integrate their expertise to provide practical advice for navigating the data science job market. Who is it for? If you're preparing for data science interviews, this book is for you. It's ideal for candidates with a foundational knowledge of Python, SQL, and statistics looking to refine and expand their technical and professional skills. Professionals transitioning into data science will also find it invaluable for building confidence and succeeding in this rewarding field.