➕ Solving Problems Using ➗ (✔Linear Regression Algorithm✔)

Data Analysis of the impact of socio-economic background on driving behavior among US teens.

Regressão Linear: Testando Relações e Prevendo Resultados

This case study uses exploratory data analysis (EDA) and regression to predict alcohol levels in wine by modeling several linear regression models with varying parameters.

A simple Multiple Regression model to predict the quality of air(AQI) using a dataset that contains Air pollutants' values of different cities of India.

An automotive manufacturer's newest prototype has been suffering from production troubles. I offered to review the production data to identify insights that may help. Within that, several statistical analyses were performed in R, including a multiple linear regression analysis to determine which variables in the dataset can be used to most accur…

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.

We know how to build a model with one X (feature variable) and Y (response variable). But what if we have three feature variables, or may be 10 or 100? Building a separate model for each of them, combining them, and then understanding them will be a very difficult and next to impossible task. By using multiple linear regression, we can build mod…

Statistical Analysis for Student Exam Scores Using SAS Studio

A classwork example in which R / R Studio is used to review production data for insights to help a manufacturing team

This report will attempt to predict the daily ozone level, our response, with a multiple regression Bayesian framework. A smoothing spline will be implemented to help make predictions and identify patterns in the data set.

The repository is about 50 Startups Prediction Project and Toyota Corolla Price prediction Project.

This project was undertaken as the culmination of our statistical learning course. Its primary objective was to utilize data from the 1990 U.S. Census to predict median house values, employing multiple regression models and advanced statistical analysis to attain precise predictions and gain valuable insights.

Predict Rental Prices from the street easy platform using Multiple Linear Regression with scikit-learm

In this project I built machine learning models using Multiple Linear Regression, Ridge regression, Lasso regression, Elasticnet regression and then created a pickle file of the regression model which gave best accuracy

A study on 'a titanic probability' via kaggle's dataset.

This repo contains EDA of red and white wine and how it relates to quality.

A statistical study to compare vehicle performance of the MechaCar vehicles against other manufacturers. Perform multiple linear regression analaysis , T-tests and collect summary statistics on various parameters.

Exercises and assignments made during a Computational Intelligence class at Federal University Of Ceará.

Statistical analysis of a product prototype using R and tidyverse. Multiple linear regressions, statistical summaries, and t-tests are used for analysis and predictions. A study is also designed to compare this product to the competition.