INFO:

Ordinary least squares (OLS) regression is a statistical method of analysis that estimates the relationship between one or more independent variables and a dependent variable; the method estimates the relationship by minimizing the sum of the squares in the difference between the observed and predicted values of the dependent variable configured as a straight line. As a follow-up to the EDA that we did last time in this video, we understand how to carefully build out our ML model using OLS and validate our model. #OLS #LinearRegression #Statsmodels 🕰️Timestamps: 0:00 - Variables description from the codebook 05:00 - First model build 16:50 - Treating NA values 21:30 - Bivariate analysis 28:00 - Statsmodel introduction 35:36 - Understanding the first results 47:45 - Model rebuilding and results 📜https://github.com/ranjiGT/Cloyster/blob/master/Regression_Analysis_Global_Pandemic_2020.ipynb 🌐 https://ourworldindata.org/coronavirus 📓Codebook: https://github.com/owid/covid-19-data/blob/master/public/data/owid-covid-codebook.csv 👍Credits: Max Roser, Hannah Ritchie, Esteban Ortiz-Ospina and Joe Hasell (2020) -