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Where the card property names are "Best", "Expected", "Worst" respectively and they have numeric values:

((Best * 2) + (Expected * 4) + (Worst * 2)) / 6

giving twice as much weighting to the expected value than to the best or worst.

Where the card property names are "Start Date" and "Duration" respectively:

"Start Date" + Duration

resulting in a date which is [duration] number of days after the Start Date.

Where the card property names are "Start Date" and "End Date" respectively:

"Start Date" - "End Date"

resulting in a number which is the number of days between Start Date and End Date.

Where the card property names are "Start Date" and "End Date" respectively:

("Start Date" - "End Date") / 7

resulting in a number which is the number of weeks between Start Date and End Date.

Where the card property name is "Planned Dev Days", and the rate of development yesterdays_weather would be replaced with the actual numeric value:

yesterdays_weather * "Planned Dev Days"

resulting in a number which is the number of points that may be expected given the developer days in the iteration and the current rate of delivery.

Where the card property name is "Estimate", and the rate of development yesterdays_weather would be replaced with the actual numeric value:

Estimate / yesterdays_weather

resulting in a number which is the number of days that the task may be expected to take to complete given the current rate of delivery.

Where the aggregate story card properties are, "Total Task Estimate" and "Completed Task Estimate":

"Completed Task Estimate"/"Total Task Estimate" * 100

resulting in a number which is the % completeness of a story.

Where the aggregate feature card property "Total Estimate of Must Stories" is used with a numeric representing cost per point:

"Total Estimate of Must Stories" * 99

resulting in a number which estimates the cost of the Must stories in a feature.