Risk of Bronchitis by Pollution, Age, Geography or Time

Problems around Panel Data (Fixed and Random Effects) and Instrumental Variables

Problem set for Econ-Stats Tutorial. Exercises from Principles of Econometrics, Chapters 10 and 15.

A Complete Step-by-step Analysis of ActBlue Donors to Bernie Sander’s Election Campaign During 2015-2016, Deriving Insights About States of Engagement of Donors, Contribution Patterns, and Their Predicted Lifetime Value

This project presents a framework for modeling user engagement states as a Markov chain, using it for prediction of future engagement states and calculating a predicted Discounted Lifetime Value for each engagement group. This notebook is a tutorial demonstrating how I applied this analysis framework to ActBlue donations data and how you (or other interested readers) could utilize this framework to your own choice of data. I apply this to the political/non-profit realm - analyzing the patterns of donations for democratic elections campaigns through ActBlue (an online donations platform), based on data of donations to Bernie Sanders’ campaign during April 2015 - February 2016.

This project presents a framework for modeling user engagement states as a Markov chain, using it for prediction of future engagement states and calculating a predicted Discounted Lifetime Value for each engagement group. This notebook is a tutorial demonstrating how I applied this analysis framework to ActBlue donations data and how you (or other interested readers) could apply this framework to your own dataset. I apply this to the political / non-profit realm - analyzing the patterns of donations for democratic elections campaigns through ActBlue (an online donations platform), based based data on donors to Bernie Sanders’ campaign during April 2015 - February 2016.

Capstone Project – Actblue Donations – Markov Engagement States Analysis 1

Econometrics/Stats Collection of exercises from Principles of Econometrics

Have you ever wondered what makes some TED talks more popular than others? Well, I’ve analyzed a dataset of 2550 ted talks to get some answers for this question. May aim was to explore which of my available variables of a given talk, such as the number of comments, number of languages translated, duration of the talk, number of tags, or day it was published online– are a strong predictor of its popularity, measured in number of views.