Proceedings of the 2019 5th International Conference on Social Science and Higher Education (ICSSHE 2019)

A New Method for Solving a Class of Limit Problems in Statistical Analysis Teaching

Authors
Xiaonan Xiao
Corresponding Author
Xiaonan Xiao
Available Online August 2019.
DOI
10.2991/icsshe-19.2019.31How to use a DOI?
Keywords
statistical analysis, teaching, limit problem, new method of solving
Abstract

Statistical analysis is a branch of mathematics with rich content and wide application. Based on the theory of probability and mathematical statistics, it studies random phenomena by analyzing the data obtained from experiments or observations to achieve various reasonable estimations and inferences on the objective regularity of the research objects. Therefore, it is necessary to collect, organize and analyze the random data effectively, and to make as accurate and satisfactory an analysis as possible of the observed problems. In this way we build a necessary foundation for further solving practical problems.

Copyright
© 2019, 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 2019 5th International Conference on Social Science and Higher Education (ICSSHE 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
August 2019
ISBN
10.2991/icsshe-19.2019.31
ISSN
2352-5398
DOI
10.2991/icsshe-19.2019.31How to use a DOI?
Copyright
© 2019, 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  - Xiaonan Xiao
PY  - 2019/08
DA  - 2019/08
TI  - A New Method for Solving a Class of Limit Problems in Statistical Analysis Teaching
BT  - Proceedings of the 2019 5th International Conference on Social Science and Higher Education (ICSSHE 2019)
PB  - Atlantis Press
SP  - 1097
EP  - 1099
SN  - 2352-5398
UR  - https://doi.org/10.2991/icsshe-19.2019.31
DO  - 10.2991/icsshe-19.2019.31
ID  - Xiao2019/08
ER  -