Which measure is best utilized when the data has extreme scores?

The median is the most suitable measure of central tendency when the data set contains extreme scores, also known as outliers. This is because the median is less affected by extreme values compared to other measures such as the mean.

When calculating the mean, extreme scores can significantly skew the result, making it unrepresentative of the overall data. For instance, if there is a very high or very low score in the data, the mean will shift towards that outlier, potentially providing a misleading average.

On the other hand, the median, which is the middle value when the data is arranged in ascending order, remains stable regardless of those extreme scores. It effectively reflects the center of the data distribution without being disproportionately influenced by the extremes. This property makes it particularly useful in situations where outliers are present, allowing for a more accurate understanding of the typical value in the data set.

The mode, while also robust to extreme values, only indicates the most frequently occurring score, which might not provide a comprehensive view of the data distribution. The weighted mean incorporates a weighting factor for some values but still can be affected by extreme scores in the same way as the regular mean. Thus, choosing the median allows for a clear and representative measure of central tendency