Car Price Prediction and Analysis - Clustering and Predictive Model

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Assignment Task

The variable definitions are provided below

VAR

DEFINITION

Ad ID

SERIAL NUMBER

Car Name

NAME - SUBJECTIVE

Make

CAR COMPANY

Model

CAR NAME

Year

YEAR OF MAKE

KM's driven

SELF EXPLANATORY

Price

PRICE QUOTED IN THE PLATFORM

Fuel

SELF EXPLANATORY

Registration city

SELF EXPLANATORY

Car documents

SELF EXPLANATORY

Assembly

LOCAL vs IMPORTED

Transmission

SELF EXPLANATORY

Condition

SELF EXPLANATORY

Seller Location

SELF EXPLANATORY

Description

SUBJECTIVE

Car Features

SUBJECTIVE

 

Question 1

  1. Perform a clustering on the

  2. How many clusters do you think the data has?

  3. What are the cluster characteristics?

Question 2

  1. Develop a predictive model that predicts the price of the car quoted in the platform

  2. What is the R-Square and Adjusted R-Square of the Model?

  3. How do I build the model and what are the list of explanatory variables for the model?

  4. Suppose I want to re-phrase the above problem as predicting the price for an ‘Expensive’ vs ‘non-expensive’ car. How do I change the model specification and how would I define the cut-off and why?

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Applicable Time Zone is AEST [Sydney, NSW] (GMT+11)
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