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Price Forecasting Models For Jmp Group Inc Jmp Stock
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Book Synopsis Linear Regression Analysis with JMP and R by : Rachel T. Silvestrini
Download or read book Linear Regression Analysis with JMP and R written by Rachel T. Silvestrini and published by Quality Press. This book was released on 2018-04-26 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive but low-cost textbook is intended for use in an undergraduate level regression course, as well as for use by practitioners. The authors have included some statistical details throughout the book but focus on interpreting results for real applications of regression analysis. Chapters are devoted to data collection and cleaning; data visualization; model fitting and inference; model prediction and inference; model diagnostics; remedial measures; model selection techniques; model validation; and a case study demonstrating the techniques outlined throughout the book. The examples throughout each chapter are illustrated using the software packages R and JMP. At the end of each chapter, there is a tutorial section demonstrating the use of both R and JMP. The R tutorial contains source code and the JMP tutorial contains a step by step guide. Each chapter also includes exercises for further study and learning.
Book Synopsis Building Better Models with JMP Pro by : Jim Grayson
Download or read book Building Better Models with JMP Pro written by Jim Grayson and published by SAS Institute. This book was released on 2015-08-01 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Practical Data Analysis with JMP by : Robert Carver
Download or read book Practical Data Analysis with JMP written by Robert Carver and published by SAS Press. This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Practical Data Analysis with JMP" uses the powerful interactive and visual approach of JMP to introduce readers to the logic and methods of statistical thinking and data analysis. The book can stand on its own or be used to supplement a standard introduction-to-statistics textbook.
Book Synopsis Practical Data Analysis with JMP, Third Edition by : Robert Carver
Download or read book Practical Data Analysis with JMP, Third Edition written by Robert Carver and published by SAS Institute. This book was released on 2019-10-18 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the concepts and techniques of statistical analysis using JMP Practical Data Analysis with JMP, Third Edition, highlights the powerful interactive and visual approach of JMP to introduce readers to statistical thinking and data analysis. It helps you choose the best technique for the problem at hand by using real-world cases. It also illustrates best-practice workflow throughout the entire investigative cycle, from asking valuable questions through data acquisition, preparation, analysis, interpretation, and communication of findings. The book can stand on its own as a learning resource for professionals, or it can be used to supplement a college-level textbook for an introductory statistics course. It includes varied examples and problems using real sets of data. Each chapter typically starts with an important or interesting research question that an investigator has pursued. Reflecting the broad applicability of statistical reasoning, the problems come from a wide variety of disciplines, including engineering, life sciences, business, and economics, as well as international and historical examples. Application Scenarios at the end of each chapter challenge you to use your knowledge and skills with data sets that go beyond mere repetition of chapter examples. New in the third edition, chapters have been updated to demonstrate the enhanced capabilities of JMP, including projects, Graph Builder, Query Builder, and Formula Depot.
Book Synopsis Data Mining for Business Analytics by : Galit Shmueli
Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2019-10-14 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Author : Publisher :Cengage Learning ISBN 13 :0357715985 Total Pages :1218 pages Book Rating :4.3/5 (577 download)
Download or read book written by and published by Cengage Learning. This book was released on with total page 1218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Business Statistics for Competitive Advantage with Excel and JMP by : Cynthia Fraser
Download or read book Business Statistics for Competitive Advantage with Excel and JMP written by Cynthia Fraser and published by Springer Nature. This book was released on with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Mining for Business Analytics by : Galit Shmueli
Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2016-05-11 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® presents an applied and interactive approach to data mining. Featuring hands-on applications with JMP Pro®, a statistical package from the SAS Institute, the book uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting. Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® also includes: Detailed summaries that supply an outline of key topics at the beginning of each chapter End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material Data-rich case studies to illustrate various applications of data mining techniques A companion website with over two dozen data sets, exercises and case study solutions, and slides for instructors www.dataminingbook.com Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® is an excellent textbook for advanced undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field.
Book Synopsis Data Mining for Business Analytics by : Galit Shmueli
Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2016-04-18 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: An applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition "...full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing."– Research Magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." – ComputingReviews.com "Excellent choice for business analysts...The book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.
Download or read book Restaurant Finance Monitor written by and published by . This book was released on 2002 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Why Startups Fail by : Tom Eisenmann
Download or read book Why Startups Fail written by Tom Eisenmann and published by Currency. This book was released on 2021-03-30 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want your startup to succeed, you need to understand why startups fail. “Whether you’re a first-time founder or looking to bring innovation into a corporate environment, Why Startups Fail is essential reading.”—Eric Ries, founder and CEO, LTSE, and New York Times bestselling author of The Lean Startup and The Startup Way Why do startups fail? That question caught Harvard Business School professor Tom Eisenmann by surprise when he realized he couldn’t answer it. So he launched a multiyear research project to find out. In Why Startups Fail, Eisenmann reveals his findings: six distinct patterns that account for the vast majority of startup failures. • Bad Bedfellows. Startup success is thought to rest largely on the founder’s talents and instincts. But the wrong team, investors, or partners can sink a venture just as quickly. • False Starts. In following the oft-cited advice to “fail fast” and to “launch before you’re ready,” founders risk wasting time and capital on the wrong solutions. • False Promises. Success with early adopters can be misleading and give founders unwarranted confidence to expand. • Speed Traps. Despite the pressure to “get big fast,” hypergrowth can spell disaster for even the most promising ventures. • Help Wanted. Rapidly scaling startups need lots of capital and talent, but they can make mistakes that leave them suddenly in short supply of both. • Cascading Miracles. Silicon Valley exhorts entrepreneurs to dream big. But the bigger the vision, the more things that can go wrong. Drawing on fascinating stories of ventures that failed to fulfill their early promise—from a home-furnishings retailer to a concierge dog-walking service, from a dating app to the inventor of a sophisticated social robot, from a fashion brand to a startup deploying a vast network of charging stations for electric vehicles—Eisenmann offers frameworks for detecting when a venture is vulnerable to these patterns, along with a wealth of strategies and tactics for avoiding them. A must-read for founders at any stage of their entrepreneurial journey, Why Startups Fail is not merely a guide to preventing failure but also a roadmap charting the path to startup success.
Download or read book The Hollywood Reporter written by and published by . This book was released on 2007 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to the Practice of Statistics by : David S. Moore
Download or read book Introduction to the Practice of Statistics written by David S. Moore and published by W H Freeman & Company. This book was released on 2009 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new Sixth Edition brings the acclaimed IPS approach to a new generation, with a number of enhancements in the text and with breakthrough media tools for instructors and students. It demonstrates how statistical techniques are used to solve real-world problems, combining real data and applications with innovative pedagogy, both in the text and via electronic media. New Format Options Introduction to the Practice of Statistics, Sixth Edition is available as: • A core book containing the first 13 chapters in hardcover (1-4292-1622-0) or paperback (1-4292-1621-2). Companion chapters 14-17 are available on the book's CD and web site. • Extended Version (hardcover; includes chapters 1-15): 1-4292-1623-9
Book Synopsis Exchange-Traded Funds in Europe by : Adam Marszk
Download or read book Exchange-Traded Funds in Europe written by Adam Marszk and published by Academic Press. This book was released on 2019-03-18 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exchange-Traded Funds in Europe provides a single point of reference on a diverse set of regional ETF markets, illuminating the roles ETFs can play in risk mitigation and speculation. Combining empirical data with models and case studies, the authors use diffusion models and panel/country-specific regressions-as well as graphical and descriptive analyses- to show how ETFs are more than conventional, passive investments. With new insights on how ETFs can improve market efficiency and how investors can benefit when using them as investment tools, this book reveals the complexity of the world's second largest ETF market and the ways that ETFs are transforming it.
Download or read book Industry Illustrated ... written by and published by . This book was released on 1923 with total page 1132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Traffic Engineering & Control written by and published by . This book was released on 1960 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Predictive Modeling by : Max Kuhn
Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
