TY  - GEN
ED  - Harvard Business Review Press
TI  - HBR guide to data analytics basics for managers: understand the numbers, make better decisions, present and persuade
T2  - Harvard business review guides
SN  - 9781633694286
U1  - 658.4033 23
PY  - 2018///
CY  - Boston, Massachusetts : 
PB  - Harvard Business Review Press, 
KW  - SLSH
KW  - Management -- Statistical methods.
KW  - Decision making -- Statistical methods
KW  - Quantitative research
KW  -  Decision support systems.
KW  - Information visualization
N1  - Includes index; ntroduction: Why you need to understand data analytics
Section 1. Getting started: Keep up with your quants: an innumerate's guide to navigating big data /​ by Thomas H. Davenport
A simple exercise to help you think like a data scientist: an easy way to learn the process of data analytics /​ by Thomas C. Redman
Section 2. Gather the right information: Do you need all that data?: questions to ask for a focused search /​ by Ron Ashkenas
How to ask your data scientists for data and analytics: factors to keep in mind to get the information you need /​ by Michael Li, Madina Kassengaliyeva, and Raymond Perkins
How to design a business experiment: tips for using the scientific method /​ by Oliver Hauser and Michael Luca
Know the difference between your data and your metrics: understand what you're measuring /​ by Jeff Bladt and Bob Filbin
The fundamentals of A/​B testing: how it works and mistakes to avoid /​ by Amy Gallo
Can your data be trusted?: gauge whether your data is safe to use /​ by Thomas C. Redman
Section 3. Analyze the data: A predictive analytics primer: look to the future by looking at the past /​ by Thomas H. Davenport
Understanding regression analysis: evaluate the relationship between variables /​ by Amy Gallo
When to act on a correlation, and when not to: assess your confidence in your findings and the risk of being wrong /​ by David Ritter
Can machine learning solve your business problem?: steps to take before investing in AI /​ by Anastassia Fedyk
A refresher on statistical significance: check if your results are real or just luck /​ by Amy Gallo
Linear thinking in a nonlinear world: a common mistake that leads to errors in judgment /​ by Bart de Langhe, Stefano Puntoni, and Richard Larrick
Pitfalls of data-driven decisions: the cognitive traps to avoid /​ by Megan MacGarvie and Kristina McElheran
Don't let your analytics cheat the truth: always ask for the outliers /​ by Michael Schrage
Section 4. Communicate your findings: Data is worthless if you don't communicate it: tell people what it means /​ by Thomas H. Davenport
When data visualization works, and when it doesn't: not all data is worth the effort /​ by Jim Stikeleather
How to make charts that pop and persuade: questions to help give your numbers meaning /​ by Nancy Duarte
Why it's so hard for us to communicate uncertainty: illustrating
and understanding
the likelihood of events: an interview with Scott Berinato /​ by Nicole Torres
Responding to someone who angrily challenges your data: ensure the data is thorough, then make them an ally /​ by Jon M. Jachimowicz
Decisions don't start with data: influence others through story and emotion /​ by Nick Morgan
N2  - 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
ER  -