GitHub topics: ols-regression | Ecosyste.ms: Repos

zyra121/advertising-sales-prediction

This repository showcases a linear regression analysis using the Advertising dataset, demonstrating both simple and multiple regression techniques in Python. It also features a custom implementation of Gradient Descent for a deeper understanding of the concepts. 🐱💻📊

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mjavadg/Econometrics_Spring-2025

Python tutorials, lecture materials, and assignments for the Econometrics course taught to Master's students in Economics at Allameh Tabataba'i University.

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JuliaStats/MultivariateStats.jl

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

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faosorios/fastmatrix

Fast computation of some matrices useful in statistics

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codelones/advertising-sales-prediction

A demo project to explore linear regression using the Advertising dataset.

Language: Python - Size: 375 KB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 2 - Forks: 0

marcelomijas/econometrics-cheatsheet

Econometrics cheat sheets with a concise review of the subject, going from the basics of an econometric model to the solution of the most popular problems.

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tvercamer/VUB-masterproef-YouTube-UvVl

De gebruikte code bij mijn masterproef aan de VUB (Bedrijfskunde)

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MUSA-Zhanchao/MUSA5000-spatial-correlation

Assignment 2 for MUSA 5000

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federicofanini/bric

Ordinary Least Squares (OLS) analysis of the relationship between economic growth and human development in BRIC countries (Brazil, Russia, India, and China) from 2000 to 2019.

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computerspieler/OLS-CUDA

An OLS estimation written with CUDA

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eafranke/Quant1-Paper-Replication

Academic research paper replication steps, including data and syntax files converted for use in SPSS, developed as teaching resources for Bentley University's Quantitative Analysis I course. These materials were created in my role as a Teaching Assistant under the guidance of Professor Clifton Chow.

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TatevKaren/econometric-algorithms

Popular Econometrics content with code; Simple Linear Regression, Multiple Linear Regression, OLS, Event Study including Time Series Analysis, Fixed Effects and Random Effects Regressions for Panel Data, Heckman_2_Step for selection bias, Hausman Wu test for Endogeneity in Python, R, and STATA.

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LouisaKoschny/Do-Trade-Unions-Pay-Off

This project uses multiple linear regression analysis to assess the impact of trade union membership on annual income using data from the Northern Ireland Life and Times Survey. Methods include descriptive statistics, multiple linear regression, and goodness-of-fit analysis to assess the union wage effect.

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GabrielIamato/spotify_musics_analysis

Analysis of Popular Songs on Spotify (2023) - A data-driven exploration of the most streamed songs, uncovering trends, correlations, and insights using Python, data visualization, and statistical techniques.

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Katyayani09/medicare_campaigns_marketmixmodels

This repository explores Market Mix Modeling to analyze the causal impact of marketing strategies on sales performance using statistical analysis and OLS regression. It helps businesses optimize campaign investments by distinguishing causation from correlation.

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s1dewalker/Model_Validation

Model Management in Python. Steps involved in Model Validation and tuning. Testing Model Assumptions in Factor Analysis with OLS Regression.

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b-knight/olspow

Python package for conducting power analysis for experiments using regression and/or clustered data.

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cynthiaxu04/causal-sleep-study

a causal sleep study on the effects of visible light on sleep quality

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garfsters/Real-Estate-Price-Prediction

Using OLS regression (and Ridge and Lasso to compare), we worked on a project that uses a dataset to predict housing prices based on user inputs on house details.

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mjavadg/Econometrics_Fall-2024

For master’s students in mathematical economics, focusing on econometric methods and applications.

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AbdirayimovS/Multiple_Regression_project

Apex team`s multiple regression project. It contains: What is Multiple Regression? Advantages and disadvantages of multiple regression, least square method and real implementation.

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fosetorico/pH_level_forecasting

End-to-End Project for pH Level Forecasting of Well Water Samples in Malawi, Conducted by Leeds Beckett University

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SantiagoEnriqueGA/custom_linear_learning

This repository focuses on building linear regression algorithms from scratch using only Numpy for faster array processing.

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mateoservent/coefeasy

Coefeasy is an R package under development for making regression coefficients more accessible. With this tool, you can read and report key coefficients instantly.

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Milanpeter-77/Coursework-Yacht-Pricing

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Szymon-Czuszek/Quantitative-Suite

Welcome to the Data Analysis and Econometrics repository! This space is dedicated to providing examples and snippets for applying econometric methods using various tools such as Python, R, GRETL, Excel, and more.

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youssef-laouina/Predicting-Apartments-Prices-in-Buenos-Aires

Machine learning project predicting real estate prices in Buenos Aires, utilizing advanced techniques for outlier detection, heteroskedasticity handling, and model optimization

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larenwell/ai-ml-pycaret-beerhub-challenge

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

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imildositoe/python_snippets

Python regression and probabilities snippets

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PranavlovesData/ExcelR_Data_Science_Assignments

This repository contains all the assignments and related files for excelR data science and machine learning course.

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Niteshchawla/Jamboree-LinearRegression

Analysis will help Jamboree in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.

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puffdapaz/IPEApython

Além de explorar boas práticas em python, o propósito é de aplicar conceitos de Arquitetura Medallion, programação orientada a objetos e ETL, utilizando dados públicos sociais dos municípios brasileiros. Este repositório utiliza ainda DuckDB e Streamlit para exibição dos resultados

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rakeshjasti/Car-MPG

Predicting miles per gallon (MPG) for a car using UCI dataset

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nvlinhvn/water-consumption-campaign-analytics

Evaluate the effectiveness of water consumption campaign in 12 districts

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nmcintyre5/supervisedLearningFinalProject

Supervised Learning project aimed at using various features to predict life expectancy.

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NajiAboo/MachineLearning

Machine Learning algorithms and models

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MarkoDojkic/Application-of-probability-and-statistics-methods

Final exam project for probability and statistics course.

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shwetapardhi/Assignment-05-Multiple-Linear-Regression-2

Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in t

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shwetapardhi/Assignment-04-Simple-Linear-Regression-2

Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

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shwetapardhi/Assignment-04-Simple-Linear-Regression-1

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi

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mugunthdinesh/FINA6337-Computational-Methods-in-Finance

This GitHub repository hosts assignments covering key financial analysis topics such as OLS regression, time series analysis, ARIMA and VAR models, and CAPM. Ideal for students and professionals seeking practical insights into finance, it offers a concise resource for honing analytical skills in financial modeling and forecasting.

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Szafranerio/California-Housing-PricesHousing-Price-Prediction-with-Linear-Regression

🤖Housing Price Prediction with Linear Regression

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Ashutosh27ind/linearRegressionMediaCompanyCaseStudy

Data Science Project : A digital media company (similar to Voot, Hotstar, Netflix, etc.) had launched a show. Initially, the show got a good response, but then witnessed a decline in viewership. The company wants to figure out what went wrong.

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Ashutosh27ind/Ecom-Market-Mix-Model

To build a MMM for ElecKart Ontario based ecommerce company

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Ashutosh27ind/Data_Deciphers---Unilever-Sales-EQ-Data-Science-POC-Use-Case---Deep-Tech-Machine-Learning

Determination of major drivers of sales and forecasting sales for next 6 periods

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piyush-multiplexer/Machine_Learning_Data

ML algorithms in Python

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aeturrell/specification_curve

Specification Curve is a Python package that performs specification curve analysis: exploring how a coefficient varies under multiple different specifications of a statistical model.

Language: Python - Size: 4.13 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 17 - Forks: 4

lorenzoridolfi9/Apple

Apple revenue forecast

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sumony2j/Linear_Regression

Explore a collection of linear regression projects showcasing implementations and applications in Python. From simple linear regression to advanced techniques like ridge and polynomial regression, this repository offers hands-on examples with diverse datasets.

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gepapago/Empirical-Research

Basic methodologies of Empirical Research applied on various case studies (R language)

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Onyango-S/Movie-Revenue-Patterns-through-Budget-Analysis

This project aims to uncover insights from the connection between movie budgets and gross revenue in the film industry.

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Onyango-S/Housing_Prices_correlation

OLS Regression on housing dataset

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green-jade/iMOD-analysis

imod 이력자료 데이터 분석/수요예측모형

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nitinjosephrepo/Conjoint-Analysis-to-uncover-consumer-preferences

Conjoint analysis is a data informed approach to understanding what consumers prefer about a product

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ShaikRiyazSandy/Simple-Linear-Regression

Simple Linear Regression

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damaniayesh/Insurance_Regression_Prediction

The project provides a Regression on the Insurance Prediction Data which shows the features of individuals, tuned using Ridge & Lasso.

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amanraghuvanshi/MultiLinear-Regression---Bike-Sharing-Analysis

MultiLinear Model - US Bike Rental Company

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Nandhakumar-rg/Abalone-OLS-and-Tree-Regression

This repository contains an in-depth analysis of the Abalone dataset using OLS and Tree-based regression models. The models are evaluated based on their MSE and R2 scores.

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Niblick1020/LinearHousingPredictor

This repository contains the Python script for predicting housing prices using linear regression models.

Language: Python - Size: 254 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

DerekEgenti/Basic-Linear-Regression-

A project showcasing the various steps involved in carrying out a basic linear regression task for prediction of a target variable.

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WilliamHope2020/GDP-Time-Series-in-R

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

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iamcrj/Multiple_Linear_Regression

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

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boyla950/predicting-the-pound

MSc Finance dissertation project at Newcastle University. This project focused on forecasting the volatility of exchange rates involving the Great British Pound using EWMA, GARCH-type and Implied Volatility models.

Language: Python - Size: 2.16 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

varungopithallapelly/Effect-of-Apps-on-Users

Applying econometric analysis to observe the effect of paid & free apps developed by small, medium & large firms app developers on total number of active users

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Prem-98/Simple-Linear-Regression

simple linear regression assignment

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Maheshwari1990/-Prediction-with-Multiple-Regression-

Multiple Linear Regression Dataset Name - 50_startups data.

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ashishyadav24092000/RBD__FabricStrength

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%..

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ashishyadav24092000/MultipleLinearRegression_TruckingCompany

Multiple Linear Regression modelling for a sample data trucking.xlsx

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ashishyadav24092000/MultipleLinearRegression_CategoricalVariables2

This explains the code for multiple regression model for a sample data saved as dummy2.xlsx. It explains the variability of model i.e. dependency of salary on Experience of Employee and their Gender. It also clarifies whether the average salary for the female employees are lesser than male employees or not.And if yes than by how much.

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ashishyadav24092000/TensileStrength_VS_hardness_DieCastAluminium

This regression model subtly explain how much the variability in tensile strength of the die cast alumnium can be explained with the help of its hardness.It gives an overall regression model as well as a training,tetsing regression models. It uses various python libraries and methds like -sklearn,statsmodel.api,train_test_split,sklearn.metrics,pandas,numpy,scipy,linear_model,OLS,regression.

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ashishyadav24092000/MAximumLIkelihoodEstimator2_TVads_and_carsold

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.

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ashishyadav24092000/Transform_Dep_Vars_regression

In this notebook we would try to modify or transform our dependent variable to rectify the model and at last create a better suited regression model as compared to other. We will just take the natural logarithm of the dependent variable and it will solve the problem of conical spread of datapoints in standard residual plot. It means that our current model has varying variance and needs to be rectified.

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ashishyadav24092000/MultipleLinearRegression_CategoricalVariables

This python code shows howw regression is handled in case of categorical variables using duumies. It calculates the multiple regression code and shows the regression table. It also performs the residual analysis.

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ashishyadav24092000/LinearRegression2_Tvads_and_CarSales

This project infers the insight that how the TV ads for cars and car Sales are being linked with each other. It is linear regression model that provides a linear regression equation or a relationship between the independent variable-number of tv ads and the dependent variable-Number of cars sold.It uses the python Libraries sklearn,statsmodels.api for OLS method and add_Constant method,pandas library for creating and fetching data_frame,numpy library,scpiy.

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ashishyadav24092000/Curvilinear_models

Here we will learn how to identify a curvilinear model and how to do the modelling for that using OLS(Ordiniary Least Square) method. Plotting residual plots for the models.

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vaitybharati/Simple-linear-Reg-1

Simple-linear-Reg-1

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vaitybharati/P26.-Supervised-ML---Multiple-Linear-Regression---Cars-dataset

Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.

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vaitybharati/P25.-Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data

Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.

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vaitybharati/P24.-Supervised-ML---Simple-Linear-Regression---Newspaper-data

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

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vaitybharati/Assignment-05-Multiple-Linear-Regression-2

Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years.

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vaitybharati/Assignment-04-Simple-Linear-Regression-1

Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regression.

Language: Jupyter Notebook - Size: 43 KB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 3 - Forks: 6

anna-dang/mod02-linear-regression

House price predictive modeling using linear regression techniques. My first modeling project! Skills demonstrated: Pandas, feature engineering, standardization, encoding, interpreting model performance/error, visualizations.

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north0n-FI/Multivariate-Regression---King-County-House-Prices

Supervised Machine Learning Using Regression Analysis

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vaitybharati/P27.-Supervised-ML---Multiple-Linear-Regression---Toyoto-Cars

Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.

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olmallet81/URT

Fast Unit Root Tests and OLS regression in C++ with wrappers for R and Python

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AScick/Machine_Learning_Project

Bunch of exercises computed during the Machine Learning for Finance course.

Language: R - Size: 2.87 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

sumeetkotaria11/BitcoinAnalysis

This project is aimed at analyzing and predicting Bitcoin price fluctuation using Natural Language Processing on Twitter data and subsequently applying VADER sentiment analysis.

Language: Jupyter Notebook - Size: 1.2 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 2 - Forks: 1

ZhenyuWangg/-Regression-Analysis-and-Modeling-Research-on-Education-Between-Income

Conducted a comprehensive research project focused on regression analysis and modeling to explore the relationship between income and education.

Size: 423 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

sahilichake/Indian-Crime-Data-Analysis-Forecasting

Conducted data analysis, statistical analysis, and data visualization on an Indian crime dataset. Applied various machine learning algorithms to gain insights from the data. Utilized Time-Series models for prediction and forecasting based on the crime data analysis.

Language: Jupyter Notebook - Size: 1.32 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

tedsters/machine-learning

machine learning projects and datasets

Language: Jupyter Notebook - Size: 30.2 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 1

omledufromage/Intro-to-Econometrics-Python-assignment

Python programming assignment developing a simulation study and exploring the OLS estimator.

Language: Python - Size: 974 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

RyanAlbertson/Ordinary_Least_Squares_Regression

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

Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

chiru30/Dr.Crypto Fork of Timsal123/HTM

An interactive site to all crypto investors out there where it connects the broken bridge of market research . To invest on any crypto coin a ton of factors contribute for right , safe and secure investment .

Language: Jupyter Notebook - Size: 3.62 MB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

vaitybharati/Assignment-04-Simple-Linear-Regression-2

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Language: Jupyter Notebook - Size: 45.9 KB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 8 - Forks: 9

LazarosAntonios/Step-by-Step-OLS-regression

This is a simple Excel file that explains thoroughly, all the steps to a Simple Linear Regression model via the OLS method. I use basic excel commands for matrix multiplication and matrix inversion. The input data are not drown from anywhere and are used as an example for the better understanding of the procedure.

Size: 26.4 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0