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Author: Cynthia Fraser
Publisher: Springer
ISBN: 3030203743
Category : Business & Economics
Languages : en
Pages : 419
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Book Description
The revised Fifth Edition of this popular textbook is redesigned with Excel 2019 and the new inclusion of interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers. Students learn to build models, produce statistics, and translate results into implications for decision makers. The text features new and updated examples and assignments, and each chapter discusses a focal case from the business world which can be analyzed using the statistical strategies and software provided in the text. Paralleling recent interest in climate change and sustainability, new case studies concentrate on issues such as the impact of drought on business, automobile emissions, and sustainable package goods. The book continues its coverage of inference, Monte Carlo simulation, contingency analysis, and linear and nonlinear regression. A new chapter is dedicated to conjoint analysis design and analysis, including complementary use of regression and JMP. For access to accompanying data sets, please email author Cynthia Fraser at
[email protected].
Author: Cynthia Fraser
Publisher: Springer
ISBN: 3030203743
Category : Business & Economics
Languages : en
Pages : 419
Get Book Here
Book Description
The revised Fifth Edition of this popular textbook is redesigned with Excel 2019 and the new inclusion of interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers. Students learn to build models, produce statistics, and translate results into implications for decision makers. The text features new and updated examples and assignments, and each chapter discusses a focal case from the business world which can be analyzed using the statistical strategies and software provided in the text. Paralleling recent interest in climate change and sustainability, new case studies concentrate on issues such as the impact of drought on business, automobile emissions, and sustainable package goods. The book continues its coverage of inference, Monte Carlo simulation, contingency analysis, and linear and nonlinear regression. A new chapter is dedicated to conjoint analysis design and analysis, including complementary use of regression and JMP. For access to accompanying data sets, please email author Cynthia Fraser at
[email protected].
Author: Cynthia Fraser
Publisher: Springer Nature
ISBN: 3031425553
Category :
Languages : en
Pages : 291
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Book Description
Author: Cynthia Fraser
Publisher: Springer
ISBN: 3319321854
Category : Business & Economics
Languages : en
Pages : 482
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Book Description
The revised Fourth Edition of this popular textbook is redesigned with Excel 2016 to encourage business students to develop competitive advantages for use in their future careers as decision makers. Students learn to build models using logic and experience, produce statistics using Excel 2016 with shortcuts, and translate results into implications for decision makers. The textbook features new examples and assignments on global markets, including cases featuring Chipotle and Costco. A number of examples focus on business in emerging global markets with particular emphasis on emerging markets in Latin America, China, and India. Results are linked to implications for decision making with sensitivity analyses to illustrate how alternate scenarios can be compared. The author emphasises communicating results effectively in plain English and with screenshots and compelling graphics in the form of memos and PowerPoints. Chapters include screenshots to make it easy to conduct analyses in Excel 2016. PivotTables and PivotCharts, used frequently in business, are introduced from the start. The Fourth Edition features Monte Carlo simulation in four chapters, as a tool to illustrate the range of possible outcomes from decision makers’ assumptions and underlying uncertainties. Model building with regression is presented as a process, adding levels of sophistication, with chapters on multicollinearity and remedies, forecasting and model validation, auto-correlation and remedies, indicator variables to represent segment differences, and seasonality, structural shifts or shocks in time series models. Special applications in market segmentation and portfolio analysis are offered, and an introduction to conjoint analysis is included. Nonlinear models are motivated with arguments of diminishing or increasing marginal response.
Author: Theodore T. Allen
Publisher: Springer Science & Business Media
ISBN: 1849960003
Category : Technology & Engineering
Languages : en
Pages : 573
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Book Description
Lean production, has long been regarded as critical to business success in many industries. Over the last ten years, instruction in six sigma has been increasingly linked with learning about the elements of lean production. Introduction to Engineering Statistics and Lean Sigma builds on the success of its first edition (Introduction to Engineering Statistics and Six Sigma) to reflect the growing importance of the "lean sigma" hybrid. As well as providing detailed definitions and case studies of all six sigma methods, Introduction to Engineering Statistics and Lean Sigma forms one of few sources on the relationship between operations research techniques and lean sigma. Readers will be given the information necessary to determine which sigma methods to apply in which situation, and to predict why and when a particular method may not be effective. Methods covered include: • control charts and advanced control charts, • failure mode and effects analysis, • Taguchi methods, • gauge R&R, and • genetic algorithms. The second edition also greatly expands the discussion of Design For Six Sigma (DFSS), which is critical for many organizations that seek to deliver desirable products that work first time. It incorporates recently emerging formulations of DFSS from industry leaders and offers more introductory material on the design of experiments, and on two level and full factorial experiments, to help improve student intuition-building and retention. The emphasis on lean production, combined with recent methods relating to Design for Six Sigma (DFSS), makes Introduction to Engineering Statistics and Lean Sigma a practical, up-to-date resource for advanced students, educators, and practitioners.
Author: Douglas A. Lind
Publisher:
ISBN: 9780072402841
Category : Commercial statistics
Languages : en
Pages : 0
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Book Description
Accompanying CD-ROM contains ... "data files, Web links, practice quizzes, PowerPoint, video clips, software tutorials, MegaStat for Excel software and user manual."--Page 4 of cover.
Author: Cynthia Fraser
Publisher: Springer Science & Business Media
ISBN: 1441998578
Category : Business & Economics
Languages : en
Pages : 470
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Book Description
Exceptional managers know that they can create competitive advantages by basing decisions on performance response under alternative scenarios. To create these advantages, managers need to understand how to use statistics to provide information on performance response under alternative scenarios. This updated edition of the popular text helps business students develop competitive advantages for use in their future careers as decision makers. Students learn to build models using logic and experience, produce statistics using Excel 2010 with shortcuts, and translate results into implications for decision makers. The author emphasizes communicating results effectively in plain English and with compelling graphics in the form of memos and PowerPoints. Statistics, from basics to sophisticated models, are illustrated with examples using real data such as students will encounter in their roles as managers. A number of examples focus on business in emerging global markets with particular emphasis on China and India. Results are linked to implications for decision making with sensitivity analyses to illustrate how alternate scenarios can be compared. Chapters include screenshots to make it easy to conduct analyses in Excel 2010 with time-saving shortcuts expected in the business world. PivotTables and PivotCharts, used frequently in businesses, are introduced from the start. Monte Carlo simulation is introduced early, as a tool to illustrate the range of possible outcomes from decision makers’ assumptions and underlying uncertainties. Model building with regression is presented as a process, adding levels of sophistication, with chapters on multicollinearity and remedies, forecasting and model validation, autocorrelation and remedies, indicator variables to represent segment differences, and seasonality, structural shifts or shocks in time series models. Special applications in market segmentation and portfolio analysis are offered, and an introduction to conjoint analysis is included. Nonlinear models are motivated with arguments of diminishing or increasing marginal response, and a chapter on logit regression models introduces models of market share or proportions. The Second Edition includes more explanation of hypothesis tests and confidence intervals, how t, F, and chi square distributions behave. The Data Files, Solution Files, and Chapter PowerPoints: The data files for text examples, cases, lab problems and assignments are stored on Blackboard and may be accessed using this link: https://blackboard.comm.virginia.edu/webapps/portal/frameset.jsp Instructors can gain access to the files, as well as solution files and chapter PowerPoints by registering on the Springer site: http://www.springer.com/statistics/business%2C+economics+%26+finance/book/978-1-4419-9856-9?changeHeader Business people can gain access to the files by emailing the author
[email protected]. https://blackboard.comm.virginia.edu/webapps/portal/frameset.jsp Instructors can gain access to the files, as well as solution files and chapter PowerPoints by registering on the Springer site: http://www.springer.com/statistics/business%2C+economics+%26+finance/book/978-1-4419-9856-9?changeHeader Business people can gain access to the files by emailing the author
[email protected].
Author: Cynthia Fraser
Publisher: Springer Science & Business Media
ISBN: 1461473810
Category : Business & Economics
Languages : en
Pages : 458
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Book Description
Exceptional managers know that they can create competitive advantages by basing decisions on performance response under alternative scenarios. To create these advantages, managers need to understand how to use statistics to provide information on performance response under alternative scenarios. This updated edition of the popular text helps business students develop competitive advantages for use in their future careers as decision makers. Students learn to build models using logic and experience, produce statistics using Excel 2013 with shortcuts, and translate results into implications for decision makers. The author emphasizes communicating results effectively in plain English and with compelling graphics in the form of memos and PowerPoints. Statistics, from basics to sophisticated models, are illustrated with examples using real data such as students will encounter in their roles as managers. A number of examples focus on business in emerging global markets with particular emphasis on emerging markets in Latin America, China and India. Results are linked to implications for decision making with sensitivity analyses to illustrate how alternate scenarios can be compared. Chapters include screenshots to make it easy to conduct analyses in Excel 2013 with time-saving shortcuts expected in the business world. PivotTables and PivotCharts, used frequently in businesses, are introduced from the start. The Third Edition features Monte Carlo simulation in three chapters, as a tool to illustrate the range of possible outcomes from decision makers’ assumptions and underlying uncertainties. Model building with regression is presented as a process, adding levels of sophistication, with chapters on multicollinearity and remedies, forecasting and model validation, autocorrelation and remedies, indicator variables to represent segment differences, and seasonality, structural shifts or shocks in time series models. Special applications in market segmentation and portfolio analysis are offered, and an introduction to conjoint analysis is included. Nonlinear models are motivated with arguments of diminishing or increasing marginal response.
Author: James T. McClave
Publisher:
ISBN: 9781292227085
Category :
Languages : en
Pages : 888
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Book Description
For courses in Introductory Business Statistics. Now in its 13th Edition, Statistics for Business and Economics introduces statistics in the context of contemporary business. Emphasizing statistical literacy in thinking, the text applies its concepts with real data and uses technology to develop a deeper conceptual understanding. Examples, activities, and case studies foster active learning in the classroom while emphasizing intuitive concepts of probability and teaching students to make informed business decisions. The 13th Edition continues to highlight the importance of ethical behaviour in collecting, interpreting, and reporting on data, while also providing a wealth of new and updated exercises and case studies.
Author: Galit Shmueli
Publisher: John Wiley & Sons
ISBN: 1118729277
Category : Mathematics
Languages : en
Pages : 560
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Book Description
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.
Author: John W. Foreman
Publisher: John Wiley & Sons
ISBN: 1118839862
Category : Business & Economics
Languages : en
Pages : 432
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Book Description
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.
