R-Language interpretation of multivariate linear regression model

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Objective

In this paper, an R language is followed to interpret a linear regression model. In many practical problems of life and work, there may be more than one factor affecting the dependent variable, such as a conclusion that the higher the level of knowledge, the higher the income levels. This may include better education because of better family conditions, because in the first-tier cities, there is a better job opportunity, and the industry catches up with the big economic upward cycle. To interpret these laws is complex, multidimensional, multivariate regression analysis method is more suitable for interpreting the law of life.

As this article is a non-statistical professional article, so when it appears that the textbook does not match the description, please take the textbook as the subject. This paper aims to introduce the knowledge of multivariate linear regression and the implementation of R language in simplified language.

Directory

1. Introduction to Multivariate linear regression

2. Meta-linear regression modeling

3. Model optimization

4. Case: Black Series Futures Day candlestick data validation

Full article: Http://blog.fens.me/r-multi-linear-regression

R-Language interpretation of multivariate linear regression model