To assess the distributions of daily high temperatures in the two cities based on the dot plots you referred to, we would need to consider several aspects such as variability, spread, overlap, and outliers.
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Variability: If the temperatures in one city vary significantly more than in the other (e.g., greater range or more extreme values), then it could be said that they have significantly different variability. Without the dot plots, it's difficult to assess this definitively.
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Similar spread: If both distributions show a similar range and spread of temperatures, then this statement could be true.
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Visual overlap of distribution: If both sets of temperatures have no unique values outside of what the other set contains, you might say that all data values overlap. However, if there are values in one distribution that are absent from the other, this would not be true.
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Outliers: Both distributions would have outliers if there are extreme values in both sets of data distinct from the rest.
Based on common characteristics in dot plots, if we observed visual overlaps, similar spread, and were able to identify outliers, the best response would likely revolve around either the similarity in spread or the presence of outliers.
Please review the actual plots to make a more informed choice. If you find that they contain similar spread, choose that option. If both have noticeable outliers, then that would be your choice.