Interpretation of Automobile Sales Statistics using R Software
An analysis of car sales data: uncovering market dynamics
Sungever, we're diggin' deep into the world of car sales data to uncover patterns and relationships that influence car prices and sales. Our dataset dabbles in various variables such as Price_in_thousands, Engine_size, Horsepower, Fuel_efficiency, Sales_in_thousands, and plenty more.
Project Objectives
Here's what we're aimin' to do with this juicy data set:
- Visualize key patterns and relationships in the data using various plots.
- Explore the distribution of car prices and sales, kepping an eye out for outliers and trends.
- Build a Random Forest regression model to predict Sales_in_thousands based on other variables in the dataset.
- Evaluate the model's performance using RMSE (Root Mean Squared Error) and Mapping Accuracy.
- Make predictions for future car sales based on a new set of features.
By the end of this project, we'll have a better understanding of the car market and the factors that drive sales in the automotive industry.
🔗 Car Sales Data *Find it
- To further enhance our data-and-cloud-computing skills, we could utilize online-education platforms for self-development and learn new techniques to analyze similar datasets like the one we're currently working on.
- In the realm of education-and-self-development, data-and-cloud-computing technology can play a crucial role in revolutionizing the sector through online-education by offering interactive learning experiences centered around real-world datasets.
