Final answer:
An extremely extreme score in a dataset is known as an outlier, which is markedly different from other data points. Outliers can influence measures like the mean but don't affect the median. The correct answer to the question is (a) An Outlier.
Step-by-step explanation:
In statistics, an outlier is a very extreme score or observation that differs significantly from the majority of data in a dataset. When examining a set of numbers, outliers can skew the results and may affect the calculated mean, median, or mode. The median is the value that separates an ordered set of data into two equal halves, but it is unaffected by outliers because it is based on the position of values, not their magnitude. The mode is the most frequently occurring value in a dataset and is not necessarily affected by outliers unless they recur with frequency. In contrast, the mean, or average, can be greatly influenced by extreme values, making it less reliable in datasets with outliers.
When analyzing data, it is essential to identify and consider outliers, as they can represent errors, unique cases, or important variations within the data. Statisticians often use different methods, such as the interquartile range (IQR) or standard deviation criteria, to detect outliers within datasets. Depending on the analysis goals, outliers might be investigated further, excluded, or used to inform about unusual conditions or trends within the data.
Given the context and definitions provided, it can be concluded that a very extreme score relative to the majority of cases in a dataset is called an outlier. Therefore, the correct option in the final answer is:
(a) An Outlier