Akaike Information Criterion or AIC is a statistical method used for **model selection**. It helps you compare **candidate models** and select the best among them.

Candidate models can be models each containing a different subset or combination of independent/predictor variables.

AIC aims to select the model which **best **explains the variance in the dependent variable with the **fewest **number of independent variables (parameters). So it helps select a **simpler **model (fewer parameters) over a **complex **model (more parameters).

**But why select a simpler model over a complex one?**

- To reduce overfitting:

We know that the more complex the model, the…

Covariance and correlation, you have probably come across these terms in probability theory and statistics. They both are used to describe a very similar aspect i.e the type of **linear relationship** between some random variables/ features. But then what are the differences between these terms and which one should you use?

To answer these questions I’ll first start by giving a brief overview of these topics. I’ll be using car specifications as an analogy for better intuition.

**Covariance**

Covariance signifies the **direction **of the linear relationship between some random variables i.e if the variables are **directly **proportionate or **inversely **proportionate…

Don’t forget to stretch comrades