Contains the complete reference for all Base SAS procedures. Provides information about what each procedure does and, if relevant, the kind of output that it produces.

This practical and thorough book explains when and how to use models and techniques for the analysis of competing risks and intermediate states. It covers the most recent insights on estimation techniques and discusses in detail how to interpret the obtained results.

Based in part on a selection of the author's past blog postings, Information Professionals' Career Confidential is a convenient, browsable, and illuminating pocket compendium of insights on topics relevant for information and knowledge professionals at any stage of their careers. This book collects comments on matters of interest to new and experienced information professionals alike in 1-2 minute “quick takes,” inviting further thought. Topics range from the value of knowledge management and effective communication in organizations to assessing employers’ perception of information professionals and how best to increase one’s value through professional organizations and volunteering. This unique resource will be illuminating for anyone in library and information science, career development, or knowledge and information management. Raises questions – in a lively and concise manner – relevant for information professionals Offers readers the opportunity to read entries one at a time for reflection, or to read the entire book and then go back to certain entries to consolidate the meaning Presents ideas and concepts from thoughtful perspectives in a style designed to make professionals and students reflect on their own careers

Explains how to increase the modularity, flexibility, and maintainability of your SAS code using the SAS macro facility. Provides complete information about macro language elements,

Describes the basics of using the SQL procedure and provides comprehensive reference information. The usage information includes retrieving data from single and multiple tables; selecting specific data from tables; subsetting, ordering, and summarizing data; updating tables; combining tables to create new tables and useful reports; performing queries on database management system (DBMS) tables; using PROC SQL with the SAS macro facility; and debugging and optimizing PROC SQL code. The reference information includes statements, dictionary components, and system options.

Learn web scraping and crawling techniques to access unlimited data from any web source in any format. With this practical guide, you’ll learn how to use Python scripts and web APIs to gather and process data from thousands—or even millions—of web pages at once. Ideal for programmers, security professionals, and web administrators familiar with Python, this book not only teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing. Code samples are available to help you understand the concepts in practice.

This unique and insightful book examines leadership within the roles of statistician and data scientist from international and diverse perspectives. Featuring contributions from leadership experts and statisticians at various stages on the career jungle gym, the text supplies a greater understanding of leadership within teams, research consulting, and project management. It encourages reflection on leadership behaviors, promoting natural and organizational leadership, identifying existing opportunities to foster creative outputs and develop strong leadership voices, and explaining how to convert a passion for statistical science into visionary, ethical, and transformational leadership.

Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more. R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide. Covers downloading, installing, and configuring R Includes tips for getting data in and out of R Offers advice on fitting regression models and ANOVA Provides helpful hints for working with graphics R For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.

Apply the tools and techniques of text analytics with ease and add value to your company by understanding its key approaches and the business reality behind them.

Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, you’ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand life’s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, you’re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles

The best-selling Little SAS Book just got even better. Readers worldwide study this easy-to-follow book to help them learn the basics of SAS programming. Now Rebecca Ottesen has teamed up with the original authors, Lora Delwiche and Susan Slaughter, to provide a new way to challenge and improve your SAS skills through thought-provoking questions, exercises, and projects. Each chapter in Exercises and Projects for The Little SAS Book is matched to a chapter in The Little SAS Book, Fifth Edition. This hands-on workbook is designed to hone your SAS skills whether you are a

student or a professional.

This book covers DATA step programming, report writing, statistical and graphical procedures, the Output Delivery System, macros, and more; contains a mixture of multiple-choice questions, open-ended discussion topics, and programming exercises with selected answers and hints; and includes comprehensive programming projects that are designed to encourage self-study and to test the skills developed by The Little SAS Book.

PIntroduces the core functionality of SAS Enterprise Miner and shows how to perform basic data mining tasks. Provides step-by-step examples that create a complete process-flow diagram including graphic results.

Provides conceptual information for the Base SAS language. Major topics include SAS keywords and naming conventions, SAS variables and expressions, error processing and debugging, SAS data sets and files, creating and customizing output, DATA step concepts and DATA step processing, reading raw data, and creating and managing SAS libraries.

Provides usage information and examples for Output Delivery System (ODS) capabilities. The document describes a wide range of formatting options and shows how to gain greater flexibility in generating, storing, and reproducing SAS procedure and DATA step output.

Explore the practical applications of predictive analytics with a focus on leveraging Rattle and Qlik Sense in your projects. From setting up your environment to constructing comprehensive data applications, this book provides a complete roadmap for mastering these tools and techniques. Gain valuable insights into your data and elevate your analytical skills for real-world business scenarios. What this Book will help me do Set up your analytics environment with Qlik Sense, R, and Rattle to kick-start your projects. Master visualization techniques and statistical methods to uncover meaningful insights. Develop data-driven predictive models and evaluate their performances effectively. Learn unsupervised and supervised machine learning techniques for diverse data problems. Build data storytelling and dashboards in Qlik Sense to showcase your results compellingly. Author(s) Ferran Garcia Pagans is a seasoned data analyst and author with extensive experience in predictive analytics and data visualization. His deep knowledge of modern analytics tools like Rattle and Qlik Sense enables him to guide professionals in deriving actionable insights from data. He excels in breaking down complex concepts into accessible knowledge, making his work invaluable for learners. Who is it for? This book is perfect for business analysts, data professionals, and enthusiasts looking to enhance their understanding of predictive analytics. It suits those with foundational knowledge of statistics and tools like Excel and R. If your goal is to implement real-world predictive models and data storytelling using Rattle and Qlik Sense, this book is an ideal companion.

Using JMP Student Edition is the official user guide for JMP Student Edition, the streamlined edition of JMP for first year statistics students. Clearly written, with easy-to-follow, step-by-step instructions, this book provides engaging illustrations and concept overviews. Chapters cover JMP basics such as importing data, creating formulas, creating graphs with Graph Builder, and performing univariate and bivariate data analysis. More complex analyses are covered, including Partition, Multiple Regression, Time Series, Design of Experiments, Variability Gauge Charts, and Quality Control, and more. JMP Student Edition software is available from major textbook publishers when packaged with their textbooks for course use.

"Learning SAP Business Objects Dashboards" is your definitive guide to mastering the creation of professional, interactive dashboards tailored for both desktop and mobile use. Whether you are starting with basics or looking to enhance your existing BI skill set, this book offers step-by-step guidance to build customizing and visually appealing dashboards using SAP Business Objects. What this Book will help me do Gain proficiency in using SAP BO Dashboard Designer to create compelling BI dashboards. Learn how to integrate data seamlessly into SAP dashboards for dynamic insights. Master the art of building interactive and responsive dashboards suitable for various devices. Explore advanced visualization techniques including maps, selectors, and styling. Understand how to ensure data security and successfully deploy your dashboards. Author(s) Taha Mahmoud is an experienced Business Intelligence consultant specializing in SAP technologies. With years of experience in crafting custom BI solutions, Taha brings a practical and approachable teaching style to the complex realm of dashboard design. His goal in writing this book is to impart practical skills to learners so they can confidently excel in their BI careers. Who is it for? This book is ideal for business analysts, BI developers, and data visualization enthusiasts aiming to learn or improve their SAP Business Objects dashboard skills. It requires basic knowledge of MS Excel and an analytical mindset. If you're tasked with presenting data in clear, impactful visuals or making interactive dashboards for your organization, this book is for you.

Mastering Matplotlib provides readers with the tools to not just create visualizations but to fully harness the capabilities of the Matplotlib library. You will explore advanced features, work on interactive visualizations, and learn to optimize plots for various platforms and datasets. By the end, you will be adept at using Matplotlib in complex projects involving data analysis and visualization. What this Book will help me do Understand the architecture and internals of Matplotlib to better utilize and extend its features. Develop visually dynamic and interactive plots that update in real-time with changes in the user interface. Leverage third-party libraries to visualize complex datasets and relationships efficiently. Create tailored styling for visualizations, meeting publication and presentation standards. Deploy and integrate Matplotlib-based visualizations into cloud environments and big data workflows seamlessly. Author(s) Duncan M. McGreggor is a seasoned software engineer with years of hands-on experience in data visualization and scientific computing. He specializes in utilizing Matplotlib for dynamic charting and advanced plotting use cases. His approach to writing focuses on empowering readers to apply and integrate visualization solutions in real-world scenarios. Who is it for? This book is ideal for scientists, software engineers, programmers, and students who have a foundational understanding of Matplotlib and are looking to take their skills to an advanced level. If you're aiming to leverage Matplotlib to handle intricate datasets or to create sophisticated visual representations, this book is for you. It caters to learners seeking practical guidance for professional or academic projects. Expand your visualization toolkit with this insightful guide.

Dive into the intersection of biology and data science with 'Bioinformatics with Python Cookbook.' This book equips you to leverage Python and its ecosystem of libraries to tackle complex challenges in computational biology, covering topics like genomics, phylogenetics, and big data bioinformatics. What this Book will help me do Understand the Python ecosystem specifically tailored for computational biology applications. Analyze and visualize next-generation sequencing data effectively. Explore and simulate population genetics for robust biological research. Utilize the Protein Data Bank to extract critical insights about proteins. Handle big genomics datasets with Python tools for large-scale bioinformatics studies. Author(s) Tiago Antao is an established bioinformatician with expertise in Python programming. With years of practical experience in computational biology, he has tailored this cookbook with detailed and actionable examples. Tiago's mission is to make bioinformatic techniques using Python accessible to researchers of varying skill levels. Who is it for? This book is ideal for researchers, biologists, and data scientists with intermediate Python skills looking to expand their expertise in bioinformatics. It caters to professionals wanting to utilize computational tools for solving biological problems. If you're involved in work or study related to genomics, phylogenetics, or large-scale biology datasets, this guide offers practical solutions. Make the most out of Python in your research journey.

"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.

Delve into the capabilities of NumPy, the cornerstone of mathematical computations in Python. In this guide, you will learn how to utilize NumPy to its fullest by exploring its powerful array and matrix operations, and also integrate it with other libraries like SciPy and matplotlib for advanced analysis and visualization. What this Book will help me do Master the installation and configuration of the NumPy library on different systems. Perform advanced array and matrix operations efficiently using NumPy. Understand and utilize commonly used NumPy modules for computational tasks. Design and generate complex plots using the matplotlib library. Learn best practices for testing and validating numerical computations with NumPy. Author(s) Ivan Idris is an experienced data analyst and Python enthusiast, proficient in utilizing numerical and scientific libraries to address complex problems. With a strong background in mathematics and computer science, Ivan brings a practical approach to his teachings. He emphasizes clarity and hands-on practice, making expert-level concepts accessible and engaging for learners. Who is it for? This book is perfect for scientists, engineers, and data professionals with a solid foundation in Python. It's meant for those seeking to deepen their understanding of numerical methods and scientific computing. If you want to harness the power of NumPy to streamline your computations and develop high-performance solutions, this guide is for you.

" 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."

Supplying a comprehensive overview of healthcare analytics research, Healthcare Data Analytics provides an understanding of the analytical techniques currently available to solve healthcare problems. The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent developments in healthcare computing and discusses emerging technologies that can help improve the health and well-being of patients. Written by prominent researchers and experts working in the healthcare domain, it sheds light on the computational challenges in the field of medical informatics.

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