Interpretation of a linear regression model by R language

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Objective

In our daily life, there are a large number of related events, such as atmospheric pressure and altitude, the higher the altitude of atmospheric pressure, the smaller the person's height and weight, generally, the higher the weight of the person is heavier. There may be related events, such as the higher the level of knowledge, the higher the level of income, the better the market economy, the stronger the currency, but the global economic crisis, gold and other safe-haven assets stronger.

If we were to study these events and find the relationships between the different variables, we would use regression analysis. Unary linear regression analysis is the simplest model to deal with the relationship between two variables, and it is a linear correlation between two variables. Let's discover the laws of life together.

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. In this paper, we try to introduce the knowledge of linear regression with simplified language, and cooperate with the implementation of R language.

Directory

1. Introduction to Unary linear regression

2. Datasets and mathematical models

3. Regression parameter estimation

4. The significance test of regression equation

5. Residual analysis and anomaly detection

6. Model prediction

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

Interpretation of a linear regression model by R language