Question: Suppose we have data regarding 30 randomly selected retall real estate parcels. Each has been measured regarding its footprint (m7) and its lease price (5).

Suppose we have data regarding 30 randomly selected retall real estate parcels. Each has been measured regarding its footprint (m7) and its lease price (5). Each has also been categorized as regards its proximity to the freeway - "Adjacent to", "No farther than 1 mile", and "Farther than 1 mile". If we decided to incorporate all this information into a regression model to predict lease price, pow many regression predictors (not including the intercept) would we need?

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