Based on your description of the scatterplot showing the relationship between the number of cups of coffee sold and temperature, here are the interpretations regarding outliers and patterns of clustering:
Clustering Patterns:
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Tightly Packed Cluster (30 to 37°F): There is a significant accumulation of data points between temperatures of 30 to 37°F and corresponding coffee sales between 42 to 48 cups. This suggests that when temperatures are in this range, an increased number of cups of coffee are sold, indicating a strong consumer preference for coffee in cooler conditions.
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Loosely Packed Cluster (40 to 51°F): A less dense group of points can be observed between the temperatures of 40 to 51°F and coffee sales between 30 to 38 cups. This indicates a moderate relationship, where coffee sales remain positive but are more variable as temperatures increase slightly, showing that not as many consumers are inclined to buy coffee at these warmer temperatures compared to the colder range.
Outliers:
- Single Outlier at 62°F: The point plotted at 62°F with only 5 cups of coffee sold can be identified as a significant outlier. In the context of the overall pattern, this point deviates from the expected trend where coffee sales typically increase as temperatures drop. This suggests that at this higher temperature, consumer demand for coffee is considerably lower, which aligns with the general expectation that warmer weather reduces hot beverage consumption.
Summary:
Overall, the scatterplot indicates a positive correlation between colder temperatures and an increase in coffee sales, with a strong concentration of sales in the 30 to 37°F range and a notable outlier at 62°F where sales are anomalously low, highlighting changing consumer behavior in relation to temperature.