| Issue |
E3S Web Conf.
Volume 224, 2020
Topical Problems of Agriculture, Civil and Environmental Engineering (TPACEE 2020)
|
|
|---|---|---|
| Article Number | 03011 | |
| Number of page(s) | 7 | |
| Section | Green IT Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202022403011 | |
| Published online | 23 December 2020 | |
Predictive modeling of indicators of the tourism sector of the world economy
1
Sochi State University, 94, Plastunskaya St., Sochi, 354000, Russia
2
Federal Research Centre the Subtropical Scientific Centre of the Russian Academy of Sciences, 2/28 Jan Fabricius St., Sochi, Russia
3
Kuban State University, 149, Stavropol St., Krasnodar, 350040, Russia
* Corresponding author: allrededor@mail.ru
The article studies the statistical indicators of the tourism sector of the world economy. For the study, predictive modeling technology is used, which includes methods of correlation and regression data analysis. A modern R programming language is used as a modeling tool, which has wide functionality. The authors analyze the main indicators of tourism, as well as predictors of scientific, technical and innovative development. As a result of the analysis, a close relationship between indicators is proved, as well as a linear relationship is identified.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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