Description

Book Synopsis

Don't let a fear of numbers hold you back.

Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. 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 three key steps in the data analysis process, so you can 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
  • Run experiments and A/B tests
  • Ask the right questions of your data experts
  • Understand statistical terms and concepts
  • Create effective charts and visualizations
  • Avoid common mistakes

HBR Guide to Data Analytics Basics for Managers

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      View other formats and editions of HBR Guide to Data Analytics Basics for Managers by

      Publisher: Harvard Business Review Press
      Publication Date: Publication Date: 03/04/2018
      ISBN13: 9781633695573, 978-1633695573
      ISBN10: 1633695573
      Also in:
      Business, Finance & Law Management decision making

      Description

      Book Synopsis

      Don't let a fear of numbers hold you back.

      Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. 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 three key steps in the data analysis process, so you can 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
      • Run experiments and A/B tests
      • Ask the right questions of your data experts
      • Understand statistical terms and concepts
      • Create effective charts and visualizations
      • Avoid common mistakes

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