Author: Linda J. Young
Publisher: Learning Express (NY)
ISBN: 9781576855355
Category : Mathematical statistics
Languages : en
Pages : 0
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Book Description
Statistics Success in 20 Minutes a Day helps both novices and knowledgeable-but-rusty students gain practical skills in statistics. Structured as a series of 20 lesson plans, the book covers all major topics in this field, such as calculating a standard score, finding the margin of errors, and making informed decisions about experiments. Hundreds of jargon-free exercises provide essential practice in solving statistics problems. Test-takers also benefit from sections on additional resources and tips for preparing for standardized tests.
Author: Darrell Huff
Publisher: W. W. Norton & Company
ISBN: 0393070875
Category : Mathematics
Languages : en
Pages : 144
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Book Description
If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.
Author: Robin H. Lock
Publisher: John Wiley & Sons
ISBN: 1119682169
Category : Mathematics
Languages : en
Pages : 866
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Book Description
Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.
Author: Bernie Devlin
Publisher: Springer Science & Business Media
ISBN: 9780387949864
Category : Social Science
Languages : en
Pages : 394
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Book Description
A scientific response to the best-selling The Bell Curve which set off a hailstorm of controversy upon its publication in 1994. Much of the public reaction to the book was polemic and failed to analyse the details of the science and validity of the statistical arguments underlying the books conclusion. Here, at last, social scientists and statisticians reply to The Bell Curve and its conclusions about IQ, genetics and social outcomes.
Author: Ivory A. Toldson
Publisher: BRILL
ISBN: 9004397043
Category : Education
Languages : en
Pages : 181
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Book Description
A Brill | Sense Bestseller! What if everything you thought you knew about Black people generally, and educating Black children specifically, was based on BS (bad stats)? We often hear things like, “Black boys are a dying breed,” “There are more Black men in prison than college,” “Black children fail because single mothers raise them,” and “Black students don’t read.” In No BS, Ivory A. Toldson uses data analysis, anecdotes, and powerful commentary to dispel common myths and challenge conventional beliefs about educating Black children. With provocative, engaging, and at times humorous prose, Toldson teaches educators, parents, advocates, and students how to avoid BS, raise expectations, and create an educational agenda for Black children that is based on good data, thoughtful analysis, and compassion. No BS helps people understand why Black people need people who believe in Black people enough not to believe every bad thing they hear about Black people.
Author: Barbara Illowsky
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 2106
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Book Description
Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.
Author: Roger Peng
Publisher:
ISBN: 9781365121975
Category : Business & Economics
Languages : en
Pages : 170
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Book Description
In this concise book you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You'll get a crash course in data science so that you'll be conversant in the field and understand your role as a leader. You'll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You'll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you'll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.
Author: Russell Walker
Publisher: Oxford University Press
ISBN: 0190260696
Category : Business & Economics
Languages : en
Pages : 313
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Book Description
Technological advancements in computing have changed how data is leveraged by businesses to develop, grow, and innovate. In recent years, leading analytical companies have begun to realize the value in their vast holdings of customer data and have found ways to leverage this untapped potential. Now, more firms are following suit and looking to monetize Big Data for big profits. Such changes will have implications for both businesses and consumers in the coming years. In From Big Data to Big Profits, Russell Walker investigates the use of Big Data to stimulate innovations in operational effectiveness and business growth. Walker examines the nature of Big Data and how businesses can use it to create new monetization opportunities. Using case studies of Apple, Netflix, Google, LinkedIn, Zillow, Amazon, and other leaders in the use of Big Data, Walker explores how digital platforms such as mobile apps and social networks are changing the nature of customer interactions and the way Big Data is created and used by companies. Such changes, as Walker points out, will require careful consideration of legal and unspoken business practices as they affect consumer privacy. Companies looking to develop a Big Data strategy will find great value in the SIGMA framework, which he has developed to assess companies for Big Data readiness and provide direction on the steps necessary to get the most from Big Data. Rigorous and meticulous, From Big Data to Big Profits is a valuable resource for students, researchers, and professionals with an interest in Big Data, digital platforms, and analytics
Author: Fred Pyrczak
Publisher: Taylor & Francis
ISBN: 1351968068
Category : Psychology
Languages : en
Pages : 513
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Book Description
• This comprehensive text covers all the traditional topics in a first-semester course. • Divided into 67 short sections, this book makes the topics easy to digest. Students regularly get positive reinforcement as they check their mastery with exercises at the end of each section. • Each exercise is based on a humorous riddle. If the answer to a riddle makes sense, students know all their answers for that exercise are correct. If not, they know they need to check their answers. • Short sections make it easy to customize your course by assigning only those sections needed to fulfill your objectives. • A comprehensive basic math review at the end of this book may be used to help students whose math skills are rusty. • Thoroughly field-tested for student interest and comprehension. The short sections and humor-based, self-checking riddles are greatly appreciated by students. • Contains Part D on effect size, which provides technical solutions to issues raised in Part C (such as the limitations of inferential statistics). New to this edition: Section 1: Explains the importance of statistical techniques in the advancement of scientific knowledge. Section 11: Provides practice with the summation operation before using it in multiple statistical tests. Section 27: This section on z-scores explains how to translate a percentile rank into a raw score. Section 30: Underlines the importance of figural representations of data, explains how to identify the most appropriate figure, and discusses how to label figures effectively. Section 41: Provides a deeper understanding of the relationship between p-values and critical values in a statistical test. Appendix J: A summary table of all statistical equations and guidelines for choosing a particular statistical test. Table 1: The format and discussion for the Table of the Normal Curve has been changed to a more conventional presentation of this statistical tool.
Author: Kristin Briney
Publisher: Pelagic Publishing Ltd
ISBN: 178427013X
Category : Computers
Languages : en
Pages : 312
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Book Description
A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin
