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

Supervised-ML---Simple-Linear-Regression---Newspaper-data. EDA and Visualization, Correlation Analysis, Model Building, Model Testing, Model predictions.

Four chemicals are being used in this problem on a fabric sample. We have to determine whether all the four chemicals are variably affecting the mean strength of fabric or not, using ANOVA and significance level = 1%..

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

Learn about Simple Linear Regression for Data Science

Basic Regression Analysis

Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon

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

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:

Imputing immunogenic phenotypes using Elastic Net to infer causality between gut microbiome and immune system.

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