Is the standard deviation influenced by extreme scores?

The statement that the standard deviation is influenced by extreme scores is accurate. Standard deviation is a measure of variability that assesses the dispersion of a set of data points around the mean. When extreme scores, often referred to as outliers, are present in a dataset, they can significantly affect the calculation of the mean, which in turn affects the standard deviation.

Extreme scores increase the range of the data and widen the spread of values, leading to a larger standard deviation. This sensitivity to outliers makes standard deviation particularly useful when assessing the distribution of data in cases where understanding variability is important, but it also means that extreme values can distort the representation of how spread out the data is.

In contrast, other measures of variability, such as the interquartile range, are less affected by extreme scores, making them potentially more robust in datasets with outliers. However, standard deviation remains a widely used statistic in many contexts where the influence of all data points, including extreme ones, is necessary for a comprehensive understanding of the dataset.