Detailed implementation of various regression analysis models and concepts on real dataset.
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Updated
Jan 15, 2024 - Jupyter Notebook
Detailed implementation of various regression analysis models and concepts on real dataset.
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon
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 de…
Estimate the impact of OIL and USD towards CPI using least squares method using R
A collaborative project looking into the likelihood of Covid-19 infection in the United States.
Streamlit app that visualizes data on CO2 emissions and GDP
Homework 1 for the INTL 601 Quantitative Research Methods Course, Prof. David Carlson, Koç University.
For a real estate firm, building a house price prediction model based upon various factors. Problem - Regression | Algorithm used -Linear Regression using OLS
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.
This project is about to use linear regression to examine the relationship between various economic variables and the mortgage rate in the United States.
Applying econometric analyses based on a videogame consoles dataset, using statistical software (Stata) and evaluate the results.
Here I have checked and removed for heteroskedasticity .
Simple Linear Regression using Ordinary Least Squares
Previsão do índice IPCA até o fim de 2025.
Used libraries and functions as follows:
Linear Regression Bike sharing Assignment
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.
Comparação entre a porcentagem de vitórias e a expectativa pitagórica na NBA.
A comparison of runtimes to fit OLS regression models using different Python libraries (Scikit-learn, statsmodels, Numpy matrix multiplication)
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