Final Project: Comparative Analysis of Fuel Efficiency in Various Vehicle Types - LIS 4273

 

Final Project: Comparative Analysis of Fuel Efficiency in Various Vehicle Types


Step 1: Choosing a Dataset

Dataset: Fuel Economy Data from the US Department of Energy (http://www.fueleconomy.gov/feg/download.shtm)

 

Step 2: Sampling and Hypothesis

Sample Size: 250 vehicles

Null Hypothesis (H0): There is no significant difference in fuel efficiency between different vehicle types.

Alternative Hypothesis (H1): There is a significant difference in fuel efficiency (MPG/City) between different vehicle types.

 

Step 3: Write-up Summary

This study aims to determine whether different types of vehicles have statistically significant differences in fuel efficiency. Customers place a high value on fuel economy, and knowledge about the capabilities of various car models can help lawmakers and consumers alike.

This study is consistent with what was discussed in class on analysis of variance (ANOVA) and hypothesis testing. The groundwork for choosing suitable statistical techniques to evaluate the differences in fuel efficiency between various car models has been laid by previously discussed subjects in class.

I will utilize an ANOVA to answer the study question. An analysis of variances in fuel economy between different types of vehicles can be done effectively with ANOVA since it permits the comparison of means across numerous groups. The type of vehicle (compact, SUV, etc.) is the categorical variable, and fuel efficiency is the continuous variable.

The following R code was used to conduct the ANOVA variance analysis:


Step 4: Generate Visualization and Abstract

Visualization

To show the distribution of fuel efficiency for each type of vehicle, I created a boxplot. A clear comparison of the fuel efficiency distribution and central tendency across different vehicle types was made possible by this graphical approach.


The purpose of this study is to determine whether there are any statistically significant differences in fuel efficiency across different vehicle classes using ANOVA. The boxplot provides insights into the possible effects on customers and the car industry by graphically illustrating the difference in fuel efficiency. The results will advance our knowledge of how different car models differ in terms of fuel efficiency, which will have consequences for consumer decisions as well as environmental concerns.

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