Basic Marketing Research Using Microsoft Excel Data Analysis

Author: Alvin C. Burns
Publisher: Pearson Education
ISBN: 9780132598965
Format: PDF, Docs
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This work utilizes Excel add-in software for data analysis, an integrated case, and experiential learning exercises to present a concise introduction to fundamentals of market research, offering resources students can use in their future careers.

Basic Marketing Research

Author: Alvin C. Burns
Publisher: Pearson College Division
ISBN: 9780135078228
Format: PDF, Docs
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A concise presentation of marketing research fundamentals. Basic Marketing Research uses an Excel add-in software for data analysis, an integrated case, and experiential learning exercises to present a concise introduction to market research fundamentals. This text also provides readers with resources they can use in their careers. The ISBN above is just for the standalone book, if you want the book/IBM® SPSS® 18.0 Integrated Student Version you shoud order the ISBN listed below. 0132490633 / 9780132490634 Basic Marketing Research with Excel & IBM® SPSS® 18.0 Integrated Student Version Package Package consists of 0132151715 / 9780132151719 IBM® SPSS® 18.0 Integrated Student Version 0135078229 / 9780135078228 Basic Marketing Research with Excel .

Consumer Behavior Building Marketing Strategy

Author: David Mothersbaugh
Publisher: McGraw-Hill Education
ISBN: 9781259232541
Format: PDF, Docs
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Consumer Behavior: Building Marketing Strategy builds on theory to provide students with a usable, strategic understanding of consumer behavior that acknowledges recent changes in internal and external influences, global marketing environments, and the discipline overall. Updated with strategy-based examples from an author team with a deep understanding of each principle's business applications, current and classic examples of both text and visual advertisements throughout the text will serve to engage students and bring the material to life. The 13th edition of Mothersbaugh/Hawkins is tech-forward in both format and content, featuring the addition of Connect's robust digital suite, including SmartBook and other assignable interactives to help students learn, apply, and expand upon core marketing concepts and make assignment management and outcomes-based reporting easy.

R for Marketing Research and Analytics

Author: Chris Chapman
Publisher: Springer
ISBN: 3319144367
Format: PDF, Docs
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This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.

Principles of Marketing Engineering and Analytics 3rd Edition

Author: Gary L. Lilien
Publisher: DecisionPro
ISBN: 098576483X
Format: PDF, Kindle
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We have designed this book primarily for the business school student or marketing manager, who, with minimal background and technical training, must understand and employ the basic tools and models associated with Marketing Engineering. The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering—putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems). We offer an accessible overview of the most widely used marketing engineering concepts and tools and show how they drive the collection of the right data and information to perform the right analyses to make better marketing plans, better product designs, and better marketing decisions. ** The latest edition includes up-to-date examples and references as well as a new chapter on the digital online revolution in marketing and its implications for online advertising. In addition, the edition now incorporates some basic financial concepts (ROI, Breakeven Analysis, and Opportunity Cost) and other tools essential to the new domain of marketing analytics. **

Data Mining for Business Analytics

Author: Galit Shmueli
Publisher: John Wiley & Sons
ISBN: 1118879333
Format: PDF, ePub, Docs
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and the first using R. 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: • Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government • 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 www.dataminingbook.com Data Mining for Business Analytics: Concepts, Techniques, and Applications in R 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 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, 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 publications including books. Peter C. Bruce is President and Founder of the Institute for Statistics Education at 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 (Wiley) and co-author of Practical Statistics for Data Scientists: 50 Essential Concepts (O’Reilly). Inbal Yahav, PhD, is Professor at the Graduate School of Business Administration at Bar-Ilan University, Israel. She teaches courses in social network analysis, advanced research methods, and software quality assurance. Dr. Yahav received her PhD in Operations Research and Data Mining from the University of Maryland, College Park. 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. Kenneth C. Lichtendahl, Jr., PhD, is Associate Professor at the University of Virginia. He is the Eleanor F. and Phillip G. Rust Professor of Business Administration and teaches MBA courses in decision analysis, data analysis and optimization, and managerial quantitative analysis. He also teaches executive education courses in strategic analysis and decision-making, and managing the corporate aviation function.

Even You Can Learn Statistics and Analytics

Author: David M. Levine
Publisher: FT Press
ISBN: 0133382680
Format: PDF, Mobi
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Thought you couldn’t learn statistics? You can – and you will! Even You Can Learn Statistics and Analytics, Third Edition is the practical, up-to-date introduction to statistics – for everyone! Now fully updated for "big data" analytics and the newest applications, it'll teach you all the statistical techniques you’ll need for finance, marketing, quality, science, social science, and more – one easy step at a time. Simple jargon-free explanations help you understand every technique, and extensive practical examples and worked problems give you all the hands-on practice you'll need. This edition contains more practical examples than ever – all updated for the newest versions of Microsoft Excel. You'll find downloadable practice files, templates, data sets, and sample models – including complete solutions you can put right to work! Learn how to do all this, and more: Apply statistical techniques to analyze huge data sets and transform them into valuable knowledge Construct and interpret statistical charts and tables with Excel or OpenOffice.org Calc 3 Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics Use probability and probability distributions Work with sampling distributions and confidence intervals Test hypotheses with Z, t, chi-square, ANOVA, and other techniques Perform powerful regression analysis and modeling Use multiple regression to develop models that contain several independent variables Master specific statistical techniques for quality and Six Sigma programs Hate math? No sweat. You’ll be amazed at how little you need. Like math? Optional "Equation Blackboard" sections reveal the mathematical foundations of statistics right before your eyes. If you need to understand, evaluate, or use statistics in business, academia, or anywhere else, this is the book you've been searching for!

Key Marketing Metrics

Author: Paul Farris
Publisher: Pearson UK
ISBN: 1292212497
Format: PDF, Mobi
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"Marketers know that they must use metrics. The key--which this book addresses superbly--is which metrics to use and how to use them." Erv Shames, Chairman, Western Connecticut Health Network; former President and CEO of Borden, Inc. and Stride Rite Corporation “50+ metrics crackles like new money…this is the best marketing book of the year.” Updated version of Strategy + Business “2006 Best Books in Marketing award winner” WHAT TO MEASURE AND HOW TO MEASURE IT TO GET THE MOST OUT OF YOUR MARKETING As the old adage goes, “If you can’t measure it, you can’t manage it.” Key Marketing Metrics is the definitive guide to today’s most valuable marketing metrics to measure the results of your marketing. In this thoroughly updated and significantly expanded book, you will understand the pros, the cons and the nuances of more than 50 of the most important metrics and know exactly how to choose the right metrics for every challenge. Key Marketing Metrics gives you a portfolio, or "dashboard", of the most valuable metrics for your business to maximise the return on your marketing investment and identify the best new opportunities for profit. Discover high-value metrics for every facet of marketing: promotional strategy, advertising, and distribution; customer perceptions; market share; competitors’ power; margins and pricing; products and portfolios; customer profitability; sales forces and channels; and more. This edition includes the latest web, online, social, and email metrics, plus new insights into measuring marketing ROI and brand equity, as well as practical advice for managing complex issues such as advertising elasticity and “double jeopardy.”

Practical Statistics by Example Using Microsoft Excel and MINITAB

Author: Terry Sincich
Publisher: Pearson College Division
ISBN: 9780130415219
Format: PDF, Kindle
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This book integrates technology into the practical introduction of statistics — both Microsoft Excel and MINITAB are incorporated as tools for data analysis. These Excel and MINITAB tutorials give users access to step-by-step instructions and screen shots for using the software to perform the statistical techniques presented in the chapter. Real-world applications and critical thinking skills are emphasized throughout that will allow readers to realize greater success in the workplace.Reorganized content — Rank tests are integrated throughout, dot plots added in Chapter 2, cumulative binomial tables added to appendix, section on the normal approximation to the binomial distribution added to Chapter 6, and goodness-of-fit test of multinomial category probabilities added to Chapter 8. For use as an introduction to statistics reference with a background in college algebra.