Review the data fields in Exhibit 6-7. What are some additional variables not contained in the dataset that could be used to predict whether customers might be satisfied?

Exhibit 6-7

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VARIABLE NAME (TYPE) Customer Id (typeless) Satisfied? (string: target) Airline Status (string) Age (numeric) Gender (string) Type of Travel (string) Shopping Amount at Airport (numeric) Eating and Drinking Amounts at Airport (numeric) Class (string) Flight Date (numeric) Day of Flight Date (date) Month of Flight Date (string) No of Flights (numeric) Airline Name (string) Flight Time (numeric) Flight Cancelled (string) Arrival Delay (numeric) Departure Delay (numeric) Origin State (string) Destination State (string) Scheduled Departure Hour (numeric) Flight Distance (numeric) DESCRIPTION Unique ID representing a customer A binary measure indicating if a customer is "satisfied" or "not satisfied" Customer's airline status (Blue, Silver, Gold, Platinum) Customer's age ranging from 15 to 85 Customer's gender (Male or Female) Business, Mileage, or Personal travelers $ amount for customer spending on shopping while at airport $ amount for customer eating and drinking expenditures while at airport Travel class (Business, Eco, Eco Plus) Date of flight Day of month for travel (1 to 31) Month of year for travel (January-December) Number of previous flights by customer Name of the flight's airline (Primera Air, Wow Air) Number of minutes the flight takes from origin city to destination city The flight was canceled or not (Yes or No) Number of minutes the flight is delayed for arrival Number of minutes the flight is delayed for departure Flight origin state Flight destination state The hour the flight is scheduled for departure (24-hour military time) Flight distance in miles