In the context of evaluating the performance of a machine learning model, understanding the spread of the dataset is crucial for assessing model robustness and generalization. Which of the following statistical measures is most directly used to evaluate the spread or dispersion of a dataset? Choose the best option.

Real Exam

Median - Represents the middle value of a dataset when ordered, useful for understanding central tendency but not spread.

9.1%

Variance - Quantifies the dispersion of data points from the mean, directly measuring how spread out the data is.

90.9%

Mean - Provides the average value of the dataset, indicating central tendency rather than spread.

0.0%

Mode - Identifies the most frequently occurring value in the dataset, unrelated to measuring spread.

0.0%

Google Professional Machine Learning Engineer