A discrete data constraint refers to data that can take on a finite or countable number of values. Let's evaluate the options provided:
a. Average score on a test - This represents continuous data because scores can take on any value within a range, including fractions or decimals.
b. Number of tests passed - This is a discrete data constraint because the number of tests passed can only be a whole number (0, 1, 2, ...).
c. Average weight of all newborns in a hospital ward - This represents continuous data since weight can take on any value within a range, including fractions.
d. Distance between points - This is also continuous data because distance can have infinite possible values, including decimals.
From this analysis, b. number of tests passed is the only example that represents a discrete data constraint with viable solutions.