Application of Linear Regression in Farmers' Income

This paper mainly discusses the application of linear regression model in the analysis of farmers' income and its influencing factors, and the application of Chinese tourism consumption in daily life. In the aspect of farmers' income, multiple linear regression model is widely used to analyze the influencing factors of farmers' income. Through the analysis of historical data and current situation, it is found that per capita wage income, per capita output value of agriculture, forestry, animal husbandry, fishery, per capita production cost expenditure, per capita transfer and property income have significant effects on farmers' income. These factors are considered to be the key to increase farmers' income, therefore, based on these analysis results, corresponding policy recommendations are put forward to promote the steady growth of farmers' income. In terms of tourism consumption, through the empirical analysis of multiple linear regression method, the research finds that rural tourism not only promotes the sales of agricultural and animal husbandry products, but also increases farmers' wage income and other sources of income, thus achieving a fundamental change in farmers' income. Linear regression model plays an important role in the analysis of farmers' income and its influencing factors, and provides a scientific basis for policy making. At the same time, the development of rural tourism has also been empirically supported by multiple linear regression method, which provides a new way for farmers to increase their income.