Advanced

Mere numbers aren't enough: A plea for Visialization

Runeson, Per LU (2016) In Perspectives on Data Science for Software Engineering p.303-309
Abstract
Quantitative data comes with enormous possibilities for presenting key characteristics of the data in a very compressed form. Basic descriptive statistics, like mean and standard deviation, comprise thousands or millions of data points into single numbers. In contrast, qualitative data, with its focus on descriptions, words, and phrases does not come with such powerful tools, leading to wordy descriptions of the analysis. However, mean and standard deviation do not bring the full understanding of the underlying phenomenon. Thus, we need visualization, or visual analytics, which combine the exactness and compactness of quantitative data with the richness and communication of qualitative communication.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Perspectives on Data Science for Software Engineering
editor
Menzies, Tim; Williams, Laurie; Zimmermann, Thomas; ; and
pages
303 - 309
publisher
Elsevier
ISBN
9780128042618
9780128042069
DOI
10.1016/B978-0-12-804206-9.00055-6
language
English
LU publication?
yes
id
befbf3c7-f25f-47dc-a5cd-468378161f3a
date added to LUP
2016-10-28 14:14:40
date last changed
2016-10-28 14:31:14
@inbook{befbf3c7-f25f-47dc-a5cd-468378161f3a,
  abstract     = {Quantitative data comes with enormous possibilities for presenting key characteristics of the data in a very compressed form. Basic descriptive statistics, like mean and standard deviation, comprise thousands or millions of data points into single numbers. In contrast, qualitative data, with its focus on descriptions, words, and phrases does not come with such powerful tools, leading to wordy descriptions of the analysis. However, mean and standard deviation do not bring the full understanding of the underlying phenomenon. Thus, we need visualization, or visual analytics, which combine the exactness and compactness of quantitative data with the richness and communication of qualitative communication. },
  author       = {Runeson, Per},
  editor       = {Menzies, Tim and Williams, Laurie and Zimmermann, Thomas},
  isbn         = {9780128042618},
  language     = {eng},
  month        = {07},
  pages        = {303--309},
  publisher    = {Elsevier},
  series       = {Perspectives on Data Science for Software Engineering},
  title        = {Mere numbers aren't enough: A plea for Visialization},
  url          = {http://dx.doi.org/10.1016/B978-0-12-804206-9.00055-6},
  year         = {2016},
}