GitHub topics: ols-regression-model
mths-andrade/brasileiro
Análise dos dados do Campeonato Brasileiro no atual formato.
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Sujith-DA279/TurtleGames_Prediction_Analysis
An in-depth analysis of a gaming retailer's customer data to improve overall sales performance through enhanced understanding of customer behavior and loyalty patterns.
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mths-andrade/inflacao
Previsão do índice IPCA até o fim de 2025.
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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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mths-andrade/dolar
Previsão da cotação do dólar até o fim de 2024.
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mths-andrade/flamengo
Avaliação sobre o ano mais efetivo do Flamengo na Libertadores desde 2019.
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mths-andrade/pyth_exp
Comparação entre a porcentagem de vitórias e a expectativa pitagórica na NBA.
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dataeducator/real_estate_linear_regression
This repository contains a Phase 2 Project for the Data Science Flex Program at the Flatiron School. This project uses linear regression, pandas, numpy and exploratory data analysis using matplotlib and seaborn to predict and analyze home prices in the King County data set..
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shwetapardhi/Assignment-05-Multiple-Linear-Regression-1
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.p
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Avinash793/regression-analysis-examples
Detailed implementation of various regression analysis models and concepts on real dataset.
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KSwaviman/Cracking-The-Personality-Code-A-Behavioral-Research
Our study focused on using the Big Five personality inventory to predict traits from students' smartphone sensor data collected over 2 months under the Horizon Europe project. Through correlation analyses and machine learning with cross-validation, we showed that predictions are reliable and accurate enough for practical use.
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Andreza-Nascimento/System-Identification
This repository contains a collection of assignments completed for the System Identification and Parameter Estimation (TIP7044) course at the Federal University of Ceará during my Master's degree.
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srushtii-m/Productivity-Prediction-in-R
Estimate factors associated with the productivity of garment manufacturing workers and perform regression analysis
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saikrishnabudi/Simple-Linear-Regression
Data Science - Simple Linear Regression Work
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jycc-267/Effects-of-COVID-19-Precautions-on-Traffic-Accidents-Taoyuan
Estimating the effects of Covid-19 Precautions on traffic accidents in Taoyuan City with Regression Discontinuity Design and the PanelOLS model from linearmodels.
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varungopithallapelly/Videogame-Consoles
Applying econometric analyses based on a videogame consoles dataset, using statistical software (Stata) and evaluate the results.
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rarooij98/VA_team10
Streamlit app that visualizes data on CO2 emissions and GDP
Language: Python - Size: 8.02 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0
ashishyadav24092000/InteractionVars_Regression
In this notebook we would be learning how to check that whether there is intercacion between two dependent variables or not. After that we would consider or add that interaction variable into our regression model and will monitor the changes in the parametrs.
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sfansaria/Machine-Learning
ols_regression, Simple_Linear_Regression,univariate_Polynomial_Regression,Bayesian_Regression
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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.
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WuCandice/-Statistical-Analysis-of-Economic-Variables-and-the-Mortgage-Rate-in-the-United-States
This project is about to use linear regression to examine the relationship between various economic variables and the mortgage rate in the United States.
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rainaa0277/House-Price-Prediction-using-Linear-Regression
For a real estate firm, building a house price prediction model based upon various factors. Problem - Regression | Algorithm used -Linear Regression using OLS
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KevinDepedri/AI-for-Finance
Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon
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vaitybharati/Assignment-05-Multiple-Linear-Regression-1
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
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avd1729/Regression-using-OLS
Simple Linear Regression using Ordinary Least Squares
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Sonaxy/Online-retail-sales-prediction 📦
Prediction of how much sales revenue expected from each customer with the website traffic data acquired from an online retailer that provides information on customer’s website visit behavior
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isiktopcu/QRMH1
Homework 1 for the INTL 601 Quantitative Research Methods Course, Prof. David Carlson, Koç University.
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jajokine/Statistics-Analysis
MITx - MicroMasters Program on Statistics and Data Science - Data Analysis: Statistical Modeling and Computation in Applications - First Project
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BiaBischoff/Capstone-Project
This is my final project for my master's degree in Data Analytics
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akash2262/P6-heteroskedasticity-checking
Here I have checked and removed for heteroskedasticity .
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PatilSukanya/Assignment-05.-Multiple-Linear-Regression-Q1
Used libraries and functions as follows:
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manasik29/Prediction-model-for-predicting-Price-of-Cars
Prediction-model-for-predicting-Price-of-Cars
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Elliott-dev/Indicators-of-Heart-Disease-Analysis
This project is about statistically analyzing risk factors for heart disease and performing A/B testing, descriptive and inferential statistics to provide health care plans and strategies to better understand the risk factors assocaited with heart disease and give key insights into what factors contribute most heavily and least heavily to the development of heart disease.
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Elliott-dev/NYC_Bike_Counts_Retrospective_Analysis
I perform a retrospective analysis on the linear regression analysis that I previously performed on the NYC Bike Counts dataset. Specifically, I analyze my linear regression analysis to identify anything that I could have done differently.
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Elliott-dev/NYC_Bike_Linear_Regression-
I used the New York Bike Counts dataset to formulate a hypothesis about the number of bikes crossing the Brooklyn Bridge. This dataset contains the number of bikes that crossed each bridge during each day. I first used this dataset to formulate a hypothesis and then used linear regression to test if my hypothesis was correct.
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raytighe/linear_regression_speeds
A comparison of runtimes to fit OLS regression models using different Python libraries (Scikit-learn, statsmodels, Numpy matrix multiplication)
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