HBR guide to data analytics basics for managers - Harvard Business Review Press (Boston, Massachusetts : Harvard Business Review Press, 2018)
Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data, but leaving the analysis to others in your company just won't cut it. Now more than ever, managers must know how to tease insight from data--to understand where it comes from, make sense of the numbers, and use those findings to inform their toughest decisions. But how do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes a three-step process to get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Formulate hypotheses and test against them Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes--
Keep up with your quants / Thomas H. Davenport -- A simple exercise to help you think like a data scientist / Thomas C. Redman -- Do you need all that data? / Ron Ashkenas -- How to ask your data scientists for data and analytics / Michael Li, Madina Kassengaliyeva, and Raymond Perkins -- How to design a business experiment / Oliver Hauser and Michael Luca -- Know the difference between your data and your metrics / Jeff Bladt and Bob Filbin -- The fundamentals of A/ B testing / Amy Gallo -- Can your data be trusted? / Thomas C. Redman -- A predictive analytics primer / Thomas H. Davenport -- Understanding regression analysis / Amy Gallo -- When to act on a correlation, and when not to / David Ritter -- Can machine learning solve your business problem? / Anastassia Fedyk -- A refresher on statistical significance / Amy Gallo -- Linear thinking in a nonlinear world / Bart De Langhe, Stefano Puntoni, and Richard Larrick -- Pitfalls of data-driven decisions / Megan MacGarvie and Kristina McElheran -- Don't let your analytics cheat the truth / Michael Schrage -- Data is worthless if you don't communicate it / Thomas H. Davenport -- When data visualization works-and when it doesn't / Jim Stikeleather -- How to make charts that pop and persuade / Nancy Duarte -- Why it's so hard for us to communicate uncertainty / An interview with Scott Berinato by Nicole Torres -- Responding to someone who challenges your data / Jon M. Jachimowicz -- Decisions don't start with data / Nick Morgan -- Appendix: Data scientist: the sexiest job of the 21st century / Thomas H. Davenport and D.J. Patil.
Includes bibliographical references and index.
Online resource; title from PDF title page (ProQuest Ebook Central, viewed November 12, 2020).
WorldCat record variable field(s) change: 650
Keywords: Management -- Statistical methods; Quantitative research; Decision making -- Statistical methods; Decision support systems; Information visualization; BUSINESS & ECONOMICS -- Industrial Management; BUSINESS & ECONOMICS -- Management; BUSINESS & ECONOMICS -- Management Science; BUSINESS & ECONOMICS -- Organizational Behavior; Decision making -- Statistical methods; Decision support systems; Information visualization; Management -- Statistical methods; Quantitative research; Electronic books