Answer:
the first option
Step-by-step explanation:
variability !
what does that word tell us ?
it means that there are more individuals differences.
you could also use "accuracy" as the opposite - we are aiming for the mean value ...
imagine some bow and arrow tournament.
who wins ?
the person with the highest accuracy across all the attempts (and that means the lowest variability in the results across all attempts relatively to the target center representing the predefined mean value).
now look at the graphic for neighborhood A.
and then for neighborhood B.
which one has the data points more clustered around the center (where the mean value is going to be) ? this one has lower variability than the one where the data points are having more than one cluster or are even all over the place.
remember, for the variability you have to add all the differences to the mean value. the smaller the differences to the mean value, the smaller the variability.
in neighborhood B almost all data points have a larger difference to the mean value.
so, the variability will be higher here.
