Senior Applied Scientist, Amazon
Senior Data Scientist, Mawdoo3 Ltd
Data Science Consultant, Fractal Analytics
Big Data & Analytics architect, Amazon
In this machine learning project, you will learn to implement Regression Discontinuity Design Example in Python to determine the effect of age on Mortality Rate in Python.
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Overview
Regression Discontinuity is a quasi-experimental evaluation method used to evaluate programs with a cutoff to determine who is eligible to participate. It allows the researcher to compare the people immediately above or below the cutoff point to identify the program's impact on a given outcome.
In this project, Regression Discontinuity Design(RDD) has been implemented in Python. The project deals with determining the effect of age on the mortality rate. You can watch the previous project of the series here Hands-On Approach to Causal Inference in Machine Learning
Aim
To understand the Regression Discontinuity Design
To determine the effect of age on the mortality rate
Dataset
The dataset contains various attributes which will be used to determine the effect of age on the mortality rate.
Tech Stack
Language: Python
Libraries: pandas, plotly, statsmodels, numpy, linearmodels
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