What does standard deviation measure in a dataset?

Standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of data values. Specifically, it provides insights into how much individual data points in a dataset deviate from the mean (average) of that dataset. A low standard deviation indicates that the data points are close to the mean, suggesting less variability, while a high standard deviation signifies that the data points are spread out over a larger range of values, indicating greater variability.

This measure is crucial in various fields, as it helps understand the consistency of data and the extent to which it fluctuates. In the context of evidence-informed practice, understanding variability is key, as it can impact the interpretation of data and the reliability of conclusions drawn from it.

The other answer choices point to different statistical concepts: central tendency pertains to measures like mean, median, or mode that indicate where the data points cluster; sample size refers to the number of observations in a dataset; and correlation relates to the strength and direction of the relationship between two variables. Each of these concepts plays a role in data analysis, but none of them captures the essence of what standard deviation specifically measures.