Amazon cover image
Image from Amazon.com

Avoiding Data Pitfalls : How to Steer Clear of Common Blunders When Working With Data and Presenting Analysis and Visualizations.

By: Publisher: Hoboken, New Jersey : John Wiley & Sons, Inc., 2020Description: xii, 258 pages ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781119278160
  • 1119278163
Subject(s): Additional physical formats: Online version:: Avoiding data pitfallsDDC classification:
  • 001.4/226 23
LOC classification:
  • QA76.9.I52 .J6639 2020
Contents:
The seven types of data pitfalls -- Pitfall 1: epistemic errors -- Pitfall 2: technical trespasses -- Pitfall 3: mathematical miscues -- Pitfall 4: statistical slipups -- Pitfall 5: analytical aberrations -- Pitfall 6: graphical gaffes -- Pitfall 7: design dangers -- Conclusion.
Summary: "Avoiding Data Pitfalls is a useful resource that points out common data viz. mistakes so that users can avoid making them and notice them when they are made by others. Working with data is so common now, but the vast majority of "data workers" were trained in another technical field like engineering or science. Most were not explicitly taught how to successfully work with today's tools and the types of data at their disposal. This book will provide illustrative examples of common mistakes, first outlining how we often think about data and the "data-reality gap," before walking the reader through each step of successful data visualization, from calculating and analyzing data to eventually presenting it in a way that is both clear and effective. The author will detail common data viz. blunders like cluttered design and ineffective use of color so that the reader can differentiate between a poor presentation and something truly representative and useful"-- Provided by publisher.
List(s) this item appears in: 2022 New Titles
Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
BOOK BOOK NCAR Library Foothills Lab QA76.9 .I52 .J6639 2020 1 Available 50583020021188
Total holds: 0

Includes index.

Includes bibliographical references and index.

The seven types of data pitfalls -- Pitfall 1: epistemic errors -- Pitfall 2: technical trespasses -- Pitfall 3: mathematical miscues -- Pitfall 4: statistical slipups -- Pitfall 5: analytical aberrations -- Pitfall 6: graphical gaffes -- Pitfall 7: design dangers -- Conclusion.

"Avoiding Data Pitfalls is a useful resource that points out common data viz. mistakes so that users can avoid making them and notice them when they are made by others. Working with data is so common now, but the vast majority of "data workers" were trained in another technical field like engineering or science. Most were not explicitly taught how to successfully work with today's tools and the types of data at their disposal. This book will provide illustrative examples of common mistakes, first outlining how we often think about data and the "data-reality gap," before walking the reader through each step of successful data visualization, from calculating and analyzing data to eventually presenting it in a way that is both clear and effective. The author will detail common data viz. blunders like cluttered design and ineffective use of color so that the reader can differentiate between a poor presentation and something truly representative and useful"-- Provided by publisher.

Questions? Email library@ucar.edu.

Not finding what you are looking for? InterLibrary Loan.