Project Overview
Collected data on sailboat models from official platforms and cleaned and preprocessed data with SPSS.
Fitted the prices of used sailboats using a linear regression model and identified key factors affecting their prices.
Compared the effects of the same factors on new and used sailboat prices through the control variable method and explored trends and patterns in value depreciation.
Compared the effects of the same factors on new and used sailboat prices through the control variable method and explored trends and patterns in value depreciation.
Assessed the generalization ability and prediction accuracy of the model via cross-validation and other tests.
Developed an automated sailboat pricing tool using Python based on the selected model and achieved the functionality of outputting predicted market prices after the inputs of sailboat parameters.
Completed the modeling and coding, wrote a 21,152-word report, and received an S designation.