STUDY PROJECT ON REGRESSION FOR EXTENT OF FOREIGN OWNERSHIP

Here for a small dataset we have used OLS(Ordiniary Least Square) and MLE(Maximum likelihood Estimation ) to calculate the regression parameters slope(b1),intercept(b0) and standard deviation of reisduals.At the end we can conclude that both the methods of estimation produces the same result.

Task 4 with Codsoft for my data science internship to predict the sales of electronic device or media

Exemplo de Regressão Linear e Não Linear (BoxCox) utilizando com visualizações gráficas do ggplot.

This repo contains various projects and assignments I worked on in my Economics Courses

Basic Regression Analysis

This assignment relates to my 6th assignment in Econ 323 - Econometrics Analysis 2. It deals with GDP time series data.

Data Science Foundations II | Statistics Fundamentals for Data Science | Simple Linear Regression for Data Science

Statistical analysis of potential association between a NBA team’s number and type of injuries to their record from the 2010-15 seasons. Prediction of 2016 season records given injury types and numbers.

Multiple Linear Regression modelling for a sample data trucking.xlsx

Used libraries and functions as follows:

This analysis modelling provides a model of 98.9% accuracy

An OLS model that predicts golf scoring average improvement using PGA tour data.

A py3 code that implements batch linear regressor using gradient descent.

Machine learning frameworks

A project from BYU's "Intro to Econometrics" class focused on data wrangling, merging, and running an OLS regression. Originally done in Stata, redone in both R and Python.

Used libraries and functions as follows:

Predicting economic mobility based on community characteristics using OLS, Ridge and Lasso regressions

supervised linear regression from scratch in javascript

Goal is to find the Prediction of Protein content, so used All Regression Algorithms of Machine Learning