The Manager's Guide to Statistics, 2018 Edition PDF Download

Author: Erol Peköz
Publisher: pekozbooks
ISBN: 0979570425
Category : Business & Economics
Languages : en
Pages : 484

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Book Description
Finally, an introduction to statistics for aspiring managers, leaders and decision makers who do not need to know all the details of statistical theory and just want real applications and commonsense explanations using words and diagrams -- without a jumble of Greek letters and mathematical formulas. The focus is on conceptual understanding, simplicity, and counterintuitive phenomena that can occur. This textbook is for an undergraduate or MBA introductory statistics course and covers summary statistics, probability, hypothesis testing, correlation, multiple regression, and includes an Excel add-in for histograms and stepwise regression. The author Erol Peköz teaches on the faculty of the Boston University School of Management and is the author of numerous technical articles and the recent book A Second Course in Probability.

Author: Erol Pekoz
Publisher: Pekozbooks
ISBN: 9780979570445
Category : Business & Economics
Languages : en
Pages : 484

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Book Description
This business statistics textbook, used in the graduate core curriculum at Wharton, Harvard, and other business schools, is for an MBA or undergraduate introductory statistics course and covers data visualization, probability, hypothesis testing, correlation, multiple regression.

Author: John Gallaugher
Publisher:
ISBN: 9781453375747
Category : Information resources management
Languages : en
Pages : 479

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Book Description

Author: Erol Pekoz
Publisher: Probabilitybookstore.com
ISBN: 9780979570476
Category : Business & Economics
Languages : en
Pages : 468

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Book Description
Finally, an introduction to statistics for aspiring managers, leaders and decision makers who do not need to know all the details of statistical theory and just want real applications and commonsense explanations using words and diagrams -- without a jumble of Greek letters and mathematical formulas. The focus is on conceptual understanding, simplicity, and counterintuitive phenomena that can occur. This textbook is for an undergraduate or MBA introductory statistics course and covers summary statistics, probability, hypothesis testing, correlation, multiple regression, and includes Excel software for histograms, correlations and stepwise regression. The author Erol Pekoz teaches on the faculty of the Boston University Questrom School of Business and is the author of numerous technical articles and the book A Second Course in Probability. Data sets and a free statistical software download are available at smgpublish.bu.edu/pekoz"

Author: Thomas J. Quirk
Publisher: Springer Nature
ISBN: 3030580016
Category : Social Science
Languages : en
Pages : 267

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Book Description
This book shows the capabilities of Microsoft Excel in teaching human resource management statistics effectively. Similar to the previously published Excel 2016 for Human Resource Management Statistics, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical human resource management problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in human resource management courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2019 for Human Resource Management Statistics: A Guide to Solving Practical Problems, 2nd Edition, capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand human resource management problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned.

Author: David S. Moore
Publisher: Palgrave Macmillan
ISBN: 1429224266
Category : Mathematics
Languages : en
Pages : 975

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Book Description
This is a clear and innovative overview of statistics which emphasises major ideas, essential skills and real-life data. The organisation and design has been improved for the fifth edition, coverage of engaging, real-world topics has been increased and content has been updated to appeal to today's trends and research.

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

Author: Ignacio Castillo
Publisher: John Wiley & Sons
ISBN: 1119983223
Category :
Languages : en
Pages : 850

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Book Description
Show students why business statistics is an increasingly important business skill through a student-friendly pedagogy. In this fourth Canadian edition of Business Statistics For Contemporary Decision Making authors Ken Black, Tiffany Bayley, and Ignacio Castillo uses current real-world data to equip students with the business analytics techniques and quantitative decision-making skills required to make smart decisions in today's workplace.

Author: Alex Reinhart
Publisher: No Starch Press
ISBN: 1593276206
Category : Mathematics
Languages : en
Pages : 177

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Book Description
Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.

Author: David Kremelberg
Publisher: SAGE Publications
ISBN: 150631791X
Category : Social Science
Languages : en
Pages : 529

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Book Description
Making statistics—and statistical software—accessible and rewarding This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS. This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.