Two-Way Data Table Analysis

The video tutorial demonstrates how to set up and use a two-way data table to analyze the impact of varying two input variables, such as response rate and price, on an output variable. It explains the setup process, including connecting the table to a model and applying conditional formatting for easier data interpretation. The tutorial also covers how to analyze the results to determine the conditions under which the output is better than a base case scenario.

What is the primary purpose of a two-way data table?

• To simplify data entry

• To create a single input-output relationship

• To vary two input variables and observe the output

• To vary one input variable and observe the output

What is the expected range for the response rate in the example?

• 1% to 8%

• 3% to 7%

• 2% to 6%

• 1% to 5%

How is the price varied in the two-way data table example?

• By 5% increments

• By $2 increments

• By 10% increments

• By $1 increments

Where should the connection to the model be placed in a two-way data table?

• Directly above the column input variable

• To the left of the row input variable

• Directly above the row input variable

• To the right of the column input variable

What are the row and column inputs in the two-way data table example?

• Row: Response Rate, Column: Average Order

• Row: Average Order, Column: Response Rate

• Row: Response Rate, Column: Price

• Row: Price, Column: Response Rate

What is a common issue with interpreting a two-way data table?

• It is too simple

• It lacks sufficient data

• It is difficult to interpret due to its size

• It is too small to analyze

What is the purpose of applying conditional formatting to the data table?

• To make the table look colorful

• To sort the data automatically

• To quickly identify better and worse outcomes

• To highlight errors in the data

In the example scenario, what response rate requires a 10% price increase to match the base case?

• 2%

• 3%

• 4%

• 5%