The Professor Proposes

Analytics Case 1

J.C. Bonilla

Context & Reference Material

This case deals with the creation of a predictive model to estimate if the professor is receiving a fair quote for an engagement ring.

Download case via Rice’s student package. You can preview the case via this attached PDF

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Professor_Proposes.pdf

117.2 kB

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Approach

Before you build a model, you need to conduct extensive exploratory data analysis (EDA).

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In your approach and EDA you need to account for the following:

1️⃣ Dummy Variable Trap

The Dummy Variable trap is a scenario in which the independent variables are multicollinear - a scenario in which two or more variables are highly correlated; in simple terms one variable can be predicted from the others.

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2️⃣ Structural breaks in the data

In statistics, a structural break is an unexpected change over time in the parameters of regression models, which can lead to huge forecasting errors and unreliability of the model in general.

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3️⃣ Goodness of Fit vs Model Correctness

Goodness of fit is how well a model can "predict" data points you've already used to estimate regression parameters. It provides predictive accuracy and describes how well a model can predict new data points, for which it hasn't yet seen the true value of the dependent variable.

Models correctness accounts for any forecasting errors as well as bias that make a model unreliable.

This is an Excel project. Meaning, the EDA and model need to be completed in Excel

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