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This assignment uses multiple linear regression to analyze factors influencing Mario Kart auction prices. The model evaluates variables such as auction duration, item condition, stock photo usage, and number of wheels. Results highlight the number of wheels as a key driver of price, while other variables show limited significance. The analysis includes model evaluation, coefficient interpretation, and a prediction for a new scenario, demonstrating the practical applications of regression with real-world data.