Based on your description of the scatterplot showing the relationship between the number of cups of coffee sold and temperature, we can identify specific patterns of clustering as well as any outliers present in the data.
Clustering Patterns:
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Tightly Packed Cluster (30°F to 37°F, 42 cups to 48 cups):
- This cluster suggests that as the temperature is relatively low (between 30°F and 37°F), there is a higher number of coffee sales, specifically around 42 to 48 cups sold. This may indicate that colder temperatures lead to increased demand for coffee, possibly due to people seeking warmth or comfort beverages.
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Loosely Packed Cluster (40°F to 51°F, 30 cups to 38 cups):
- The second cluster, which is more spread out than the first, occurs at slightly higher temperatures (40°F to 51°F) with a range of sales between 30 and 38 cups. This pattern indicates a decrease in the number of coffee sales as the temperature rises but still shows a preference for coffee in the moderate temperature range.
Outlier:
- Single Data Point (62°F, 5 cups sold):
- The point located at 62°F and 5 cups sold seems to be an outlier in this scatterplot. At this relatively high temperature, the sales of coffee drop significantly, suggesting that people are less inclined to purchase coffee when it is warmer outside (such as at 62°F). This point diverges from the observed pattern in cooler temperatures where sales were still relatively high.
Overall Interpretation:
The scatterplot indicates a trend where coffee sales increase as temperatures decrease, which aligns with common expectations regarding hot beverages. The tightly clustered data in the lower temperature range shows a stronger correlation between cooler temperatures and higher coffee sales. In contrast, higher temperatures appear to negatively impact coffee sales, as highlighted by the outlier at 62°F, where the sales drop significantly. Overall, the data suggests that temperature plays a critical role in influencing coffee consumption patterns.