Make studying statistics simple with this easy-to-read resource Wouldn't it be wonderful if studying statistics were easier? With U Can: Statistics I For Dummies, it is! This one-stop resource combines lessons, practical examples, study questions, and online practice problems to provide you with the ultimate guide to help you score higher in your statistics course. Foundational statistics skills are a must for students of many disciplines, and leveraging study materials such as this one to supplement your statistics course can be a life-saver. Because U Can: Statistics I For Dummies contains both the lessons you need to learn and the practice problems you need to put the concepts into action, you'll breeze through your scheduled study time. Statistics is all about collecting and interpreting data, and is applicable in a wide range of subject areas—which translates into its popularity among students studying in diverse programs. So, if you feel a bit unsure in class, rest assured that there is an easy way to help you grasp the nuances of statistics! Understand statistical ideas, techniques, formulas, and calculations Interpret and critique graphs and charts, determine probability, and work with confidence intervals Critique and analyze data from polls and experiments Combine learning and applying your new knowledge with practical examples, practice problems, and expanded online resources U Can: Statistics I For Dummies contains everything you need to score higher in your fundamental statistics course!

Building Better Models with JMP® Pro provides an example-based introduction to business analytics, with a proven process that guides you in the application of modeling tools and concepts. It gives you the "what, why, and how" of using JMP® Pro for building and applying analytic models. This book is designed for business analysts, managers, and practitioners who may not have a solid statistical background, but need to be able to readily apply analytic methods to solve business problems.

In addition, this book will greatly benefit faculty members who teach any of the following subjects at the lower to upper graduate level: predictive modeling, data mining, and business analytics. Novice to advanced users in business statistics, business analytics, and predictive modeling will find that it provides a peek inside the black box of algorithms and the methods used.

Topics include: regression, logistic regression, classification and regression trees, neural networks, model cross-validation, model comparison and selection, and data reduction techniques. Full of rich examples, Building Better Models with JMP Pro is an applied book on business analytics and modeling that introduces a simple methodology for managing and executing analytics projects. No prior experience with JMP is needed.

Make more informed decisions from your data using this newest JMP book.

IBM® Cognos® Business Intelligence (BI) provides a proven enterprise BI platform with an open data strategy. Cognos BI provides customers with the ability to use data from any source, package it into a business model, and make it available to consumers in various interfaces that are tailored to the task. IBM Cognos Dynamic Cubes complements the existing Cognos BI capabilities and continues the tradition of an open data model. It focuses on extending the scalability of the IBM Cognos platform to enable speed-of-thought analytics over terabytes of enterprise data, without having to invest in a new data warehouse appliance. This capability adds a new level of query intelligence so you can unleash the power of your enterprise data warehouse. This IBM Redbooks® publication addresses IBM Cognos Business Intelligence V10.2.2 and specifically, the IBM Cognos Dynamic Cubes capabilities. This book can help you in the following ways: Understand core features of the Cognos Dynamic Cubes capabilities of Cognos BI V10.2 Learn by example with practical scenarios by using the IBM Cognos samples This book uses fictional business scenarios to demonstrate the power and capabilities of IBM Cognos Dynamic Cubes. It primarily focuses on the roles of the modeler, administrator, and IT architect.

Machine Learning with R (Second Edition) provides a thorough introduction to machine learning techniques and their application using the R programming language. You'll gain hands-on experience implementing various algorithms and solving real-world data challenges, making it an invaluable resource for aspiring data scientists and analysts. What this Book will help me do Understand the fundamentals of machine learning and its applications in data analysis. Master the use of R for cleaning, exploring, and visualizing data to prepare it for modeling. Build and apply machine learning models for classification, prediction, and clustering tasks. Evaluate and fine-tune model performance to ensure accurate predictions. Explore advanced topics like text mining, handling social network data, and big data analytics. Author(s) Brett Lantz is a data scientist with significant experience as both a practitioner and communicator in the machine learning field. With a focus on accessibility, he aims to demystify complex concepts for readers interested in data science. His blend of hands-on methods and theoretical insight has made his work a favorite for both beginners and experienced professionals. Who is it for? Ideal for data analysts and aspiring data scientists who have intermediate programming skills and are exploring machine learning. Perfect for R users ready to expand their skill set to include predictive modeling techniques. Also fits those with some experience in machine learning but new to the R environment. Provides insightful guidance for anyone looking to apply machine learning in practical, real-world scenarios.

This book presents a wide variety of statistical approaches for analyzing pharmacoepidemiologic data. It covers both commonly used techniques, such as proportional reporting ratios for the analysis of spontaneous adverse event reports, and newer approaches, such as the use of marginal structural models for controlling dynamic selection bias in the analysis of large-scale longitudinal observational data. Many real examples from both mental and physical health disorders illustrate the use of the methods.

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.