The scatterplot shows two main clusters: one between 30°F and 35°F with coffee sales ranging from 42 to 48 cups, and another between 40°F and 52°F with sales from 30 to 38 cups. There is a notable outlier at 62°F, where only 5 cups were sold. Overall, the data suggests a negative correlation between temperature and coffee sales, although this trend is less evident in the 30-35°F range.
The scatterplot illustrates the relationship between the number of cups of coffee sold and the temperature in degrees Fahrenheit. The data points are clustered in two main groups. The first group is concentrated between 30°F and 35°F, with the number of cups of coffee sold ranging from approximately 42 to 48. The second group is more spread out, ranging from 40°F to 52°F, with the number of cups sold varying between 30 and 38. There is also a single outlier at 62°F, where only 5 cups of coffee were sold. Overall, the scatterplot suggests a negative correlation between temperature and coffee sales, as higher temperatures generally correspond to lower sales, though this trend is less clear within the 30-35°F range.
Shorten this down to three sentences or less without leaving any important info out(the goal is to interpret the scatterplot by describing any outliers and patters of clustering)
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