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Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Language: English
Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Gebunden. Condition: New. Highlights methodological developments in the way that data analytics is both learned and taught. Featuring extensive coverage on emerging relevant topics such as data complexity, statistics education, and curriculum development, this publication is geared .
Language: English
Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Language: English
Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Buch. Condition: Neu. Data Visualization and Statistical Literacy for Open and Big Data | Theodosia Prodromou | Buch | Gebunden | Englisch | 2017 | Information Science Reference | EAN 9781522525127 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Language: English
Published by Information Science Reference, 2017
ISBN 10: 1522525122 ISBN 13: 9781522525127
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data visualization has emerged as a serious scholarly topic, and a wide range of tools have recently been developed at an accelerated pace to aid in this research area. Examining different ways of analyzing big data can result in increased efficiency for many corporations and organizations. Data Visualization and Statistical Literacy for Open and Big Data highlights methodological developments in the way that data analytics is both learned and taught. Featuring extensive coverage on emerging relevant topics such as data complexity, statistics education, and curriculum development, this publication is geared toward teachers, academicians, students, engineers, professionals, and researchers that are interested in expanding their knowledge of data examination and analysis.