Research on the Application of Probability Statistics in Science and Engineering Courses Under the Background of Big Data
- DOI
- 10.2991/978-94-6463-012-1_50How to use a DOI?
- Keywords
- Probability and Statistics; Course Integration; Matlab Software; Data Statistics and Analysis; Nonlinear Programming
- Abstract
Probability and statistics is a highly applied subject, and its application in science and engineering courses can allow students to better understand and apply the theory and knowledge of professional courses. In order to better adapt to the training goals of compound talents, based on spss, matlab, python and other software, and based on the data in probability statistics, multiple models such as multiple regression models, nonlinear programming and ordinary differential equations are established. The results of the models are obtained respectively, and the results are analyzed in combination with specific cases to build a platform for students’ data modeling, data simulation, data analysis and data mining. It can effectively cultivate innovative new engineering and new science talents with multi-disciplinary and broad vision, and provide talents and scientific and technological support for the country’s economic and social development.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yuanyuan Mao PY - 2022 DA - 2022/12/09 TI - Research on the Application of Probability Statistics in Science and Engineering Courses Under the Background of Big Data BT - Proceedings of the 2022 International Conference on Educational Innovation and Multimedia Technology (EIMT 2022) PB - Atlantis Press SP - 451 EP - 459 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-012-1_50 DO - 10.2991/978-94-6463-012-1_50 ID - Mao2022 ER -