Proceedings of the 2018 3rd International Conference on Education, Sports, Arts and Management Engineering (ICESAME 2018)

Reflection on the Talent Training Mode Transformation of Statistics Specialty against the Background of Big Data

Authors
Xin Mu, Zhigang Li
Corresponding Author
Xin Mu
Available Online July 2018.
DOI
10.2991/icesame-18.2018.77How to use a DOI?
Keywords
Big Data, Statistics, Talent Training Mode, Transformation
Abstract

In the information explosion society, big data has entered all aspects of the social economy. Statistics, as a supporting discipline of big data, has received more and more attention. This paper expounds the basic concepts of big data and statistics specialty, analyzes on the demand of statistics major talents and the disadvantages of traditional training mode, and gives some thoughts on the training mode and transformation of statistics major talents under the background of big data. At last, the conclusion is summarized and prospected.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 3rd International Conference on Education, Sports, Arts and Management Engineering (ICESAME 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
July 2018
ISBN
978-94-6252-530-6
ISSN
2352-5398
DOI
10.2991/icesame-18.2018.77How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xin Mu
AU  - Zhigang Li
PY  - 2018/07
DA  - 2018/07
TI  - Reflection on the Talent Training Mode Transformation of Statistics Specialty against the Background of Big Data
BT  - Proceedings of the 2018 3rd International Conference on Education, Sports, Arts and Management Engineering (ICESAME 2018)
PB  - Atlantis Press
SP  - 375
EP  - 378
SN  - 2352-5398
UR  - https://doi.org/10.2991/icesame-18.2018.77
DO  - 10.2991/icesame-18.2018.77
ID  - Mu2018/07
ER  -