📊 R-AutoPrice: Predicting Car Price with R

Welcome to the captivating realm of regression analysis! This repository hosts an immersive project that dives deep into various facets of regression techniques, feature selection, and thorough analysis. Get ready to embark on a data-driven journey through a dataset that unveils the secrets of diverse car models and their prices, intricately intertwined with an array of features. Our mission? To immerse you in the art of regression intricacies, analytical methodologies, feature curation, and hands-on implementation using the beloved R programming language.

🌟 Key Features

• In-depth exploration of regression nuances, embracing diverse techniques and feature selection wizardry.
• Unravel the magic of regression analysis through real-world R implementation.
• Comprehensive documentation: Dive into the entire voyage via our output.pdf and main.Rmd files.

This spectacular project was crafted under the expert guidance of Prof. Javad B. Ebrahimi at Sharif University of Technology by the ingenious Amin Hashemi.

⭐ Unveiling the Project Objectives

This voyage is fueled by a series of impactful objectives:

1. Data Delve and Refinement: Kick off your journey by unearthing and refining the dataset. Immerse yourself in the realm of data exploration:

   • Evoke insights through enchanting box plots, unraveling the secrets of three intriguing dataset columns.
   • Master the art of handling missing data with finesse, preserving the essence of every precious data point.
   • Unlock the symphony of correlations via a visual map, seeding hypotheses waiting to be tested by eloquent t-tests.
   • Elevate your categorical variables to celestial heights through the charm of dummy variables.

2. Mastery of Multiple Regression Analysis: Unleash the potential of multiple regression analysis, a cornerstone of predictive modeling:

   • Unveil your model's prowess through a captivating array of metrics – RSS, TSS, MSE, R-Squared, and Adjusted R-Squared.
   • Decipher the significance and real-world implications of these metrics, revealing the essence behind the numbers.
   • Craft an enchanting coefficient comparison map, shedding light on the allure of high coefficients and the dance of standardized data scales.

3. Unraveling Model Performance and Insights: Ascend the heights of model performance evaluation and interpretation:

   • Illuminate your model's brilliance on the grand stage of test data evaluation.
   • Elevate your model's elegance through data scaling and feature enhancements, ushering it into the hall of predictive greatness.

4. Artistry of Feature Selection and Discernment: Embark on the journey of feature selection, guided by meticulous analysis and statistical prowess:

   • The artful tango of t-tests and p-values: Sculpt a refined feature set that augments model interpretability, revealing the secrets of the dataset.
   • The symphony of ANOVA and f-statistics: Handpick the top 10 features, orchestrating a harmonious ensemble of predictive power.
   • Synergy under the microscope: Unlock 10 pairs of variables, amplifying the intrigue and potential of your feature set.

📚 Language and Libraries

• Enchanting with R: This project is a grand affair with the R programming language.
• A Tapestry of Comments: Weave comments into your code, painting clarity across every vital line.

🗂️ Project Chronology

Our odyssey is a sequence of captivating chapters:

1. Data Unveiling and Refinement
2. The Grand Symphony of Multiple Regression Analysis
3. Unraveling the Art of Feature Selection

(Optional): 4. Exploring Alternative Horizons

With the map of our code files, you shall navigate through each section, discovering insights, and crafting a tapestry of knowledge.

Embark on this journey, for the realm of regression beckons!

With Warm Regards, Amin Hashemi Summer 2023