Knowing What You Dont Know: Choosing the Right Chart to Show Data Distributions to Non-Expert Users
Files in This Item:
File | Size | Format | |
---|---|---|---|
Download | insight_publication.pdf | 297.1 kB | Adobe PDF |
Title: | Knowing What You Dont Know: Choosing the Right Chart to Show Data Distributions to Non-Expert Users | Authors: | Zubiaga, Arkaitz; MacNamee, Brian | Permanent link: | http://hdl.handle.net/10197/7347 | Date: | 1-Jul-2015 | Online since: | 2016-01-07T13:20:38Z | Abstract: | An ability to understand the outputs of data analysis is a key characteristic of data literacy and the inclusion of data visualisations is ubiquitous in the output of modern data analysis. Several aspects still remain unresolved, however, on the question of choosing data visualisations that lead viewers to an optimal interpretation of data, especially when audiences have differing degrees of data literacy. In this paper we describe a user study on perception from data visualisations, in which we measured the ability of participants to validate statements about the distributions of data samples visualised using different chart types. We find that histograms are the most suitable chart type for illustrating the distribution of values for a variable. We contrast our findings with previous research in the field, and posit three main issues identified from the study. Most notably, however, we show that viewers struggle to identify scenarios in which a chart simply does not contain enough information to validate a statement about the data that it represents. The results of our study emphasise the importance of using an understanding of the limits of viewers’ data literacy to design charts effectively, and we discuss factors that are crucial to this end. | Type of material: | Conference Publication | Publisher: | ACM | Keywords: | Machine learning; Statistics; Data visualisation; Data literacy; User studies | Other versions: | http://websci15.org/ | Language: | en | Status of Item: | Peer reviewed | Conference Details: | Web Science 2015 Conference, Oxford, United Kingdom, 28 June - 1 July 2015 | This item is made available under a Creative Commons License: | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ |
Appears in Collections: | Insight Research Collection |
Show full item record
Page view(s) 50
1,614
Last Week
5
5
Last month
18
18
checked on Jun 25, 2022
Download(s)
170
checked on Jun 25, 2022
Google ScholarTM
Check
If you are a publisher or author and have copyright concerns for any item, please email research.repository@ucd.ie and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.