What is the best estimate of the standard deviation of the men's weights displayed in a dot plot?

To estimate the standard deviation of the men's weights shown in a dot plot, it is essential to consider the spread of the data points around the mean. The standard deviation quantifies this spread, indicating how much the weights typically deviate from the average.

When observing a dot plot, you can visualize how the weights are distributed. If the weights cluster closely around the mean, the standard deviation will be smaller. Conversely, if the weights are widely spread, then the standard deviation will be larger.

Choosing the estimate of 25 suggests that there is a substantial spread among the men's weights. If the weights vary significantly, with some weights being much lower or higher than the mean, a standard deviation around this value is reasonable.

This estimate aligns with the expected variability typical for such data, where men's weights can often range significantly due to various factors like athleticism, height, and body composition. The choice of a lower number, such as 10, would imply that the weights are tightly clustered, which is less likely given the potential diversity in men's weights.

Overall, choosing 25 as the best estimate reflects a realistic understanding of variability in this type of data, showcasing a balance between common weights and the broader spread likely observed.