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

This project focuses on the development and evaluation of machine learning models to predict credit card application and crime rate.

Multiple Linear Regression modelling for a sample data trucking.xlsx

Used libraries and functions as follows:

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.

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

Used libraries and functions as follows:

Machine learning models

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

Implemented Multiple Linear Regression using Backward Elimination Method. This code will work for all dependencies of the form y=b0+b1x1+b2x2+b3x3....bnxn