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Analysis of the Influencing Factors of the Multi-Linear Regression Model based on R Language on the Total Cost of Domestic Tourism

摘要


With the development of the country, China has entered a decisive year to build an all-round well-off society. Therefore, in order to achieve the goal of an all-round well-off society, we should pay more attention to the contribution of tourism to the national economy and it also plays an important role in the development of the rural economy. China's territory is vast and culturally diverse, so the development of tourism is full of great potential. Against the background of tourism, this paper shows the process of multiple regression modelling and the analysis method of regression model using R language to influence the total cost of tourism in China.

參考文獻


Yang Yanxiao, Chen Yaning, Kang Suoqian, Yu Xinle. Analysis of tourism revenue sources and influencing factors based on multiple linear regression models [J]. Rural Economy and Science, 2020, 31(07):118-120.
Rao Haiyang, Domestic tourist population forecast for 2020 based on BP neural network[J]. SichuanUniversity,2020. http://ffiy5657afdfcc724a3aacfa1b04bc68b170sou5fp5bu6ffx65qn.fffb. suse.cwkeji.cn:999/SubjectStudy/ArticleNew?id=137
He Xiaoqun, Liu Wenqing. Applied Regression Analysis(Fifth edition) [M]. Renmin University of China Press, 2019, 7.
Robert I. Kabacoff . R in Action(Second edition)[M]. POST & TELECOM PRESS, 2016,5 .
Wang Mengfei. Analysis of the contribution of education investment to residents' income in China [D]. Shandong University of Finance and Economics, 2017.

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