Final answer:
The mean changes when an outlier is dropped from a data set, but it can't be determined if it's now more or less than the median or mode without more details on the data's distribution.
Step-by-step explanation:
When an outlier is dropped from a data set, the value of the mean changes, but whether it is now more or less than the value of the median cannot be determined without further information about the distribution of the data. Generally, if a data set has a right skew, the mean is greater than the median, and the mode is less than both. In a left skewed distribution, the mean is less than the median, and the median is often less than the mode. Dropping an outlier will shift the mean towards the center of the remaining data, but its position relative to the median and mode depends on the direction and extent of the skewness of the original distribution. Therefore, the correct response would be: a. changes but the position relative to the median and mode can't be determined from the information. It's also worth noting that the outlier's effect on quartiles cannot be definitively concluded without additional details.