The dataset we see here contains data about 50 startups. Using regression models to predict which investment expenditures maximize profits.

Resolução das questões da 3VA da disciplina de Computação para análise de dados.

The research project titled "Investigation of the Factors That Influence the Price of Cars in the USA" aimed to identify key features that can help a new automotive manufacturing company gain a competitive edge in the highly competitive US market. Employing a quantitative research methodology, the study utilized a multiple linear regression model to analyze data from 205 car models and 26 variables, with the analysis performed using RStudio. The findings indicated that significant predictors of car prices include city mileage per gallon (mpg), horsepower, fuel system, engine size, cylinder number, fuel type, and wheel drive type. Specifically, cars with an mpfi fuel system, five and twelve cylinders, rear-wheel drive, and gas fuel type were associated with higher profitability. The study provides valuable insights for automotive companies on optimizing car design and business strategies to achieve favorable pricing outcomes in the US market.

This document is a practice in R Studio, based on the original article "Comic Books Are Still Made By Men, For Men And About Men". Published on the website fivethirtyeight.com