Proceedings of the 2017 7th International Conference on Social Network, Communication and Education (SNCE 2017)

Prediction of the Development of Science and Technology Service Industry Based on Multiple Linear Regression Analysis

Authors
Zhu Enyuan , Yan Fanhui , Jia Keliang
Corresponding Author
Zhu Enyuan 
Available Online July 2017.
DOI
10.2991/snce-17.2017.141How to use a DOI?
Keywords
Science and Technology Service Industry; Development Level; Forecast Model; Shandong Province
Abstract

In order to enhance the development of science and technology service industry in Shandong Province, the paper established a statistical index system of science and technology service industry based on the relevant literature and the actual data analysis. And then the paper used multiple linear regression model to predict the development of science & technology service industry in Shandong province. Finally the paper collected the data set and analyzed them through SPSS and putted forward to some policy suggestions to promote its development.

Copyright
© 2017, 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 2017 7th International Conference on Social Network, Communication and Education (SNCE 2017)
Series
Advances in Computer Science Research
Publication Date
July 2017
ISBN
10.2991/snce-17.2017.141
ISSN
2352-538X
DOI
10.2991/snce-17.2017.141How to use a DOI?
Copyright
© 2017, 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  - Zhu Enyuan 
AU  - Yan Fanhui 
AU  - Jia Keliang
PY  - 2017/07
DA  - 2017/07
TI  - Prediction of the Development of Science and Technology Service Industry Based on Multiple Linear Regression Analysis
BT  - Proceedings of the 2017 7th International Conference on Social Network, Communication and Education (SNCE 2017)
PB  - Atlantis Press
SP  - 694
EP  - 699
SN  - 2352-538X
UR  - https://doi.org/10.2991/snce-17.2017.141
DO  - 10.2991/snce-17.2017.141
ID  - Enyuan 2017/07
ER  -