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Statistics Toolkit
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Book Synopsis Statistics Toolkit by : Rafael Perera
Download or read book Statistics Toolkit written by Rafael Perera and published by John Wiley & Sons. This book was released on 2011-09-23 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise book will help you to interpret the statistical evidence provided by quantitative studies and to plan how to work with data in your own clinical research. Following the successful format of the Toolkit series, Statistics Toolkit guides the reader through statistical concepts using flowcharts, diagrams and real life examples to reflect concepts in a simple and practical manner. Sections include: Clear explanation of basic concepts in the context of clinical research Demonstration of how data are described, displayed and interpreted in different formats Practical glossary and key to the symbols used in statistics and a discussion of the software tools The book offers a handy, quick reference that has an easy-to-follow structure throughout, making it ideal for health care professionals and students.
Book Synopsis The Data Warehouse Toolkit by : Ralph Kimball
Download or read book The Data Warehouse Toolkit written by Ralph Kimball and published by John Wiley & Sons. This book was released on 2011-08-08 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.
Book Synopsis An Introduction to Statistical Learning by : Gareth James
Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Book Synopsis The Data Toolkit by : Robert T. Hess
Download or read book The Data Toolkit written by Robert T. Hess and published by Corwin Press. This book was released on 2011-12-01 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to accelerate analysis into action Using data for school improvement is a key goal of Race to the Top, and now is the time to make data-driven school improvement a priority. However, many educators are drowning in data. Boost your professional learning community′s ability to translate data into action with this new book from Pam Robbins and Robert T. Hess. The Data Toolkit provides ten easy-to-use tools that don′t require statistical expertise, can be implemented in a timely manner, and facilitate problem-solving at the classroom, school, and district levels. These proven methods help educators: Frame the questions Drive the conversation Engage in productive reflection Uncover understandings Create a data-driven plan Achieve and monitor results Written in an educator-friendly format each chapter contains instructions on using the tool, a sample scenario, and examples—practical resources that will help your PLC be the best it can be. Also included are case studies that show how data teams, PLCs, and individual teachers have used the book′s methods in their own settings. The culminating school improvement mapping tool guides the team through designing an action plan focused on increasing student learning and achievement outcomes.
Book Synopsis A Python Data Analyst’s Toolkit by : Gayathri Rajagopalan
Download or read book A Python Data Analyst’s Toolkit written by Gayathri Rajagopalan and published by Apress. This book was released on 2021-02-21 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the fundamentals of data analysis, and statistics with case studies using Python. This book will show you how to confidently write code in Python, and use various Python libraries and functions for analyzing any dataset. The code is presented in Jupyter notebooks that can further be adapted and extended. This book is divided into three parts – programming with Python, data analysis and visualization, and statistics. You'll start with an introduction to Python – the syntax, functions, conditional statements, data types, and different types of containers. You'll then review more advanced concepts like regular expressions, handling of files, and solving mathematical problems with Python. The second part of the book, will cover Python libraries used for data analysis. There will be an introductory chapter covering basic concepts and terminology, and one chapter each on NumPy(the scientific computation library), Pandas (the data wrangling library) and visualization libraries like Matplotlib and Seaborn. Case studies will be included as examples to help readers understand some real-world applications of data analysis. The final chapters of book focus on statistics, elucidating important principles in statistics that are relevant to data science. These topics include probability, Bayes theorem, permutations and combinations, and hypothesis testing (ANOVA, Chi-squared test, z-test, and t-test), and how the Scipy library enables simplification of tedious calculations involved in statistics. What You'll Learn Further your programming and analytical skills with Python Solve mathematical problems in calculus, and set theory and algebra with Python Work with various libraries in Python to structure, analyze, and visualize data Tackle real-life case studies using Python Review essential statistical concepts and use the Scipy library to solve problems in statistics Who This Book Is For Professionals working in the field of data science interested in enhancing skills in Python, data analysis and statistics.
Book Synopsis Statistical Tools for Measuring Agreement by : Lawrence Lin
Download or read book Statistical Tools for Measuring Agreement written by Lawrence Lin and published by Springer Science & Business Media. This book was released on 2012-10-30 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agreement assessment techniques are widely used in examining the acceptability of a new or generic process, methodology and/or formulation in areas of lab performance, instrument/assay validation or method comparisons, statistical process control, goodness-of-fit, and individual bioequivalence. Successful applications in these situations require a sound understanding of both the underlying theory and methodological advances in handling real-life problems. This book seeks to effectively blend theory and applications while presenting readers with many practical examples. For instance, in the medical device environment, it is important to know if the newly established lab can reproduce the instrument/assay results from the established but outdating lab. When there is a disagreement, it is important to differentiate the sources of disagreement. In addition to agreement coefficients, accuracy and precision coefficients are introduced and utilized to characterize these sources. This book will appeal to a broad range of statisticians, researchers, practitioners and students, in areas of biomedical devices, psychology, medical research, and others, in which agreement assessment are needed. Many practical illustrative examples will be presented throughout the book in a wide variety of situations for continuous and categorical data.
Book Synopsis Statistical Tools for Finance and Insurance by : Pavel Cizek
Download or read book Statistical Tools for Finance and Insurance written by Pavel Cizek and published by Springer Science & Business Media. This book was released on 2005-12-06 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in an accessible and engaging style, this self-instructional book makes a good use of extensive examples and full explanations. The electronic edition, allowing the reader to run, modify, and enhance all quantlets on the spot, can be downloaded at no cost via the attached license registration card.
Book Synopsis Data Visualization Toolkit by : Barrett Clark
Download or read book Data Visualization Toolkit written by Barrett Clark and published by Addison-Wesley Professional. This book was released on 2016-08-04 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create Beautiful Visualizations that Free Your Data to Tell Powerful Truths “The depth of Barrett Clark’s knowledge shines through in his writing: clear, concise, and confident. Barrett has been practicing all of this stuff in his day job for many years–Postgres, D3, GIS, all of it. The knowledge in this book is real-world and hard-earned!” –From the Foreword by Obie Fernandez Data Visualization Toolkit is your hands-on, practical, and holistic guide to the art of visualizing data. You’ll learn how to use Rails, jQuery, D3, Leaflet, PostgreSQL, and PostGIS together, creating beautiful visualizations and maps that give your data a voice and to make it “dance.” Barrett Clark teaches through real-world problems and examples developed specifically to illuminate every technique you need to generate stunningly effective visualizations. You’ll move from the absolute basics toward deep dives, mastering diverse visualizations and discovering when to use each. Along the way, you’ll build three start-to-finish visualization applications, using actual real estate, weather, and travel datasets. Clark addresses every component of data visualization: your data, database, application server, visualization libraries, and more. He explains data transformations; presents expert techniques in JavaScript, Ruby, and SQL; and illuminates key concepts associated with both descriptive statistics and geospatial data. Throughout, everything is aimed at one goal: to help you cut through the clutter and let your data tell all it can. This guide will help you Explore and understand the data visualization technology stack Master the thought process and steps involved in importing data Extract, transform, and load data in usable, reliable form Handle spotty data, or data that doesn’t line up with what your chart expects Use D3 to build pie and bar charts, scatter and box plots, and more Work effectively with time-series data Tweak Ruby and SQL to optimize performance with large datasets Use raw SQL in Rails: window functions, subqueries, and common table expressions Build chord diagrams and time-series aggregates Use separate databases or schema for reporting databases Integrate geographical data via geospatial SQL queries Construct maps with Leaflet and Rails Query geospatial data the “Rails way” and the “raw SQL way”
Book Synopsis The Statistics Toolkit by : Joel Lalone
Download or read book The Statistics Toolkit written by Joel Lalone and published by McGraw-Hill Primis Custom Publishing. This book was released on 1998-08-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is written for statistics courses for which the prerequisite is 3 years of high school math and/or a college algebra/precalculus course.The first 5 chapters are intended for a 3 credit hour course that covers statistical inference through two-variable techniques (t-tests, Chi Square, and correlation). Chapter 6 is written in reference guide format. This chapter can be used in a second 3 credit course covering ANOVA, nonparametrics, multiple regression, nonlinear regression, and an introduction t multivariate techniques.The text comes as a package, bundled with Minitab Student Release 12 and the brief Minitab manual, MEET MINITAB.
Book Synopsis Basic Statistics by : Mark Jay Kiemele
Download or read book Basic Statistics written by Mark Jay Kiemele and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2011-02-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. - Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects - Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods - Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
Book Synopsis Basic Statistical Tools for Improving Quality by : Chang W. Kang
Download or read book Basic Statistical Tools for Improving Quality written by Chang W. Kang and published by John Wiley & Sons. This book was released on 2012-08-29 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introductory book on improving the quality of a process or a system, primarily through the technique of statistical process control (SPC). There are numerous technical manuals available for SPC, but this book differs in two ways: (1) the basic tools of SPC are introduced in a no-nonsense, simple, non-math manner, and (2) the methods can be learned and practiced in an uncomplicated fashion using free software (eZ SPC 2.0), which is available to all readers online as a downloadable product. The book explains QC7 Tools, control charts, and statistical analysis including basic design of experiments. Theoretical explanations of the analytical methods are avoided; instead, results are interpreted through the use of the software.
Book Synopsis A Tool Kit for Quantitative Data Analysis by : Sotirios Sarantakos
Download or read book A Tool Kit for Quantitative Data Analysis written by Sotirios Sarantakos and published by Red Globe Press. This book was released on 2007-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Successful statistical analysis of research data is an integral part of any social sciences degree. This straightforward and accessible text provides students with both a beginners guide and a continuing reference tool for undertaking statistical analysis using SPSS. Through clear instructions and relevant examples, Sarantokas introduces key skills for every new comer to the subject, such as choosing the appropriate test, loading data, using graphs and interpreting computer outputs. Drawing on extensive data sets and pedagogical features, this book is an up to date and user-friendly guide to statistics and SPSS, which no Social Sciences student should be without.
Book Synopsis Statistics in Corpus Linguistics by : Vaclav Brezina
Download or read book Statistics in Corpus Linguistics written by Vaclav Brezina and published by Cambridge University Press. This book was released on 2018-09-20 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and accessible introduction to statistics in corpus linguistics, covering multiple techniques of quantitative language analysis and data visualisation.
Book Synopsis Modern Statistics with R by : Måns Thulin
Download or read book Modern Statistics with R written by Måns Thulin and published by CRC Press. This book was released on 2024-08-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit. It teaches you: Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. Exploratory data analysis - using visualisations and multivariate techniques to explore datasets. Statistical inference - modern methods for testing hypotheses and computing confidence intervals. Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. Ethics in statistics - ethical issues and good statistical practice. R programming - writing code that is fast, readable, and (hopefully!) free from bugs. No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book. In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com.
Book Synopsis Statistics for Health Data Science by : Ruth Etzioni
Download or read book Statistics for Health Data Science written by Ruth Etzioni and published by Springer Nature. This book was released on 2021-01-04 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students’ anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engaging explanations and examples. In this way, the authors cultivate a deep (“organic”) understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/
Book Synopsis The Analytics Lifecycle Toolkit by : Gregory S. Nelson
Download or read book The Analytics Lifecycle Toolkit written by Gregory S. Nelson and published by John Wiley & Sons. This book was released on 2018-03-07 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: An evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.
