In statistical analysis, what does a higher variance indicate?

A higher variance signifies a larger spread of data points around the mean. Variance is a statistical measure that quantifies how much the values in a data set differ from the mean of that set. When variance is high, it indicates that the data points are dispersed widely, meaning that there is a significant deviation from the average value. This increased spread allows analysts to understand that the data is not tightly clustered but rather varies greatly, which can affect predictions and interpretations of the dataset.

In contrast, lower variance would suggest that the data points are closer to the mean, indicating more consistency. The other options do not accurately reflect the implications of higher variance. For instance, greater consistency in data would relate to a lower variance, while a uniform distribution implies that the values are evenly spread rather than widely dispersed. The size of the sample or number of observations does not directly correlate with variance; a small sample can have high or low variance depending on the data's distribution.