Simple Linear Regression
In previous chapters, we worked with distributions of single variables. Now we will discuss the relationships between variables. In this chapter and the next chapter, we will investigate the relationship between two or more variables using linear regression. In this chapter, we will discuss simple linear regression within the framework of Ordinary Least Squares (OLS) regression. Simple linear regression is a very useful tool for estimating continuous values from two linearly related variables. We will provide an overview of the intuitions and calculations behind regression errors. Next, we will provide an overview of the pertinent assumptions of linear regression. After that, we will analyze the output summary of OLS in statsmodels, and finally, we will address the scenarios of serial correlation and model validation. As highlighted, our main topics in this chapter follow this framework:
- Simple linear regression using OLS
- Coefficients of correlation...
