Predicting Car Fuel Efficiency with Engine Features, This project investigates the impact of engine characteristics on car fuel efficiency, measured in miles per gallon (MPG). Given the significant role of the automobile industry in petroleum consumption and greenhouse gas emissions, improving fuel efficiency is crucial. We hypothesize that key engine features, namely the number of cylinders (cyl) and engine displacement (displ) in liters, can be valuable predictors of a car’s fuel efficiency. To test this hypothesis, we will perform a multiple regression analysis on a dataset containing 33,442 vehicle testing records with 12 quantitative and qualitative variables. From this data, we will focus on cyl, displ (explanatory variables), and combined MPG (response variable). The results of this analysis will help determine the significance of these engine features in predicting fuel efficiency. This information can be valuable for car manufacturers, policymakers, and consumers seeking to improve fuel economy and reduce environmental impact.

Statistics for Data Science

Final Project - Market Prices