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Title: Data Visualisation and Statistics from the Future
Contributor(s): Prodromou, Theodosia  (author)orcid 
Publication Date: 2013
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Abstract: Our world is increasingly data-rich and data-dependent. Every day, 2.5 quintillion bytes of data are solely created - so much that 90% of the data in the world today has been created in the last two years alone. This data can be structured and unstructured data such as text, sensor data, audio, digital pictures and videos, click streams, posts to social media sites, log files, cell phone GPS signals etc. Data visualization is commonly used to explore and effectively communicate relevant information about this voluminous data through graphic representations. The term data visualisation is related to the new field of information visualisation. This includes visualisation of all kinds of information, not just data, and is closely associated with research by computer scientists. From a statistical perspective data visualization can be viewed as computer automated exploratory data analysis of voluminous complex data sets. This data visualisation has blossomed into a multidisciplinary research area, and a wide range of visualisation tools have been developed at an accelerated pace. Admittedly, statistical data analysis necessitates data visualisation to form the basis for decision-making. New approaches are discussed so data visualisation and the flexible nature of current computing software can potentially have a major impact on the discipline of Statistics.
Publication Type: Conference Publication
Conference Details: 59th International Statistical Institute (ISI) World Statistics Congress, Hong Kong, China, 25th - 30th August, 2013
Source of Publication: 59th ISI World Statistics Congress Detailed Programme (Data visualization for youth appeal Sponsoring Association(s)), p. 1-6
Publisher: International Statistical Institute (ISI)
Place of Publication: online
Field of Research (FoR) 2008: 139999 Education not elsewhere classified
130202 Curriculum and Pedagogy Theory and Development
130309 Learning Sciences
Field of Research (FoR) 2020: undefined
390102 Curriculum and pedagogy theory and development
390408 Learning analytics
390409 Learning sciences
Socio-Economic Objective (SEO) 2008: 930199 Learner and Learning not elsewhere classified
930102 Learner and Learning Processes
930103 Learner Development
Socio-Economic Objective (SEO) 2020: undefined
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
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