A repository created to explore and understand Statistics through coding.

Assessed foreign exchange risk using multiple regression on market index and exchange rates. Explained 87% of stock return variance using regression diagnostics and Bloomberg Terminal data. OLS regression quantifying GBP/USD and GBP/EUR exposure for Energean PLC -R²=0.87 using Bloomberg Terminal data with heteroscedasticity-robust standard errors.

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Regressão Linear Simples e Múltipla com OLS | MBA Data Science USP/ESALQ

Just a place to play around with stats

Monte Carlo Study of OLS Asymptotics carried out in Stata

Conjunto de modelos de Inteligência Artificial implementados para a disciplina de IA do sexto semestre do curso de CC da Unifor (2023.2)

predicting fragility of stock markets

classicsml ⛈️🔄📉 : Classsic Supervised ML # Cost Function # Gradient Descent

This case study is for the analysis of viewers of a particular show, so that more viewers can be indulged in the show.

Used libraries and functions as follows:

Econometric study examining how COVID-19 reshaped higher education decisions across U.S. regions using OLS regression on 318,372 observations from the U.S. Census Bureau Household Pulse Survey.

Diagnostic tools for regression modeling. Julia-equivalent for diagnoser (https://github.com/robertschnitman/diagnoser).

Observe the effect of Hubble’s Law in Python using OLS Regression, Pairs Bootstrap Resampling, and Hypothesis Testing.

Implementation of Machine learning algorithms only using numpy.

The aim of this study is to model people's wages as a function of several parameters: gender, education, education of fathers, number of young children

Code and visualization utilized for my doctoral dissertation on the effects of Caribbean migration in Houston's residential inequality.

Applied econometrics in R: OLS, Probit & DiD (panel data) to estimate the impact of sales meetings on savings.

Applied Econometrics Project, Analysis conducted with R