Seems like nobody knows the answer to the quiz question?
Anyway, here is a practical example when you could make use of the above listing. Say you imported experimental data in form of a matrix of numeric values, and unfortunately some of the matrix elements are either missing, corrupt, or replaced by strings ("err", "N/A"). You decide not to bin the entire matrix but to replace those annoying :D elements in such a sensible way that you could still make use of the data for further automatic mathematical processing. This step is called data cleaning.
Example: The calculation of the column mean, i.e. the mean value of a column of a numeric matrix.
In[1]:= col = {2, 4, 8, 6, 5}; (* 5 valid elements, clean data *)
Mean[col] (* (2+4+8+6+5)/5 = 5 *)
Out[2]= 5
Now let's assume that your column has a corrupt entry, a corrupt or missing element produced by the electronic device which recorded/logged the data.
In[3]:= col = {2, 4, "N/A", 6, "N/A"}; (* 3 of 5 elements are valid, 2 are corrupt *)
Then you must take a decision how you want to proceed with the data. If you're interested in the column mean, then replacing the "N/A" with the value zero would not be a good idea, because it would warp the data (and the column mean) too much, (2+4+0+6+0)/5 = 2.4. Instead, a common procedure would be to replace all corrupt values with the (same) mean of the remaining values which is (2+4+6)/3 = 4.
In[4]:= col = {2, 4, 4, 6, 4};
Mean[col]
Out[5]= 4
However, this procedure might not be desirable for any reason. Instead, you're quizzing yourself whether the "N/A" can/cannot be replaced by a symbol which Wolfram L interprets correctly as a missing numeric value and hence calculates the correct column mean directly as (2+4+6)/3 = 4.
If you're unsure which vocab item could work here, the full list from the OP gives you a systematic way for testing. As a beginner, you would think that good candidates to start with are Missing, None, Invisible, Undefined, Null, Nothing, Empty, Removed, Gone, Exclusions, Absent, Blank, Placeholder, what do you think? ;-)