From the scatterplot, there is one outlier located at 62 degrees Fahrenheit on the horizontal axis and 5 cups of coffee sold on the vertical axis. This datum is significantly different from the rest of the data points and is considered an outlier.
In terms of clustering, there are two distinct clusters of data points. The first cluster is tightly packed between 30 to 37 degrees Fahrenheit on the horizontal axis and 42 to 48 cups of coffee sold on the vertical axis. This indicates that there is a strong positive correlation between temperature and the number of cups of coffee sold in this temperature range.
The second cluster is loosely packed between 40 to 51 degrees Fahrenheit on the horizontal axis and 30 to 38 cups of coffee sold on the vertical axis. This suggests that there is a weak positive correlation between temperature and the number of cups of coffee sold in this temperature range.
Overall, the scatterplot shows that there is a general trend of more cups of coffee being sold at higher temperatures, but there is some variability in the relationship between temperature and coffee sales in different temperature ranges.
make this like a 8th graer wrote i t
In the scatterplot, there is one weird dot at 62 degrees and 5 cups of coffee sold. It doesn't fit in with the other dots, so it's an outlier.
There are two main groups of dots. The first group is all squished together between 30 to 37 degrees and 42 to 48 cups of coffee sold. This means when it's hotter, more coffee is sold. The second group is spread out between 40 to 51 degrees and 30 to 38 cups sold. This shows that when it's warmer, more coffee is sold, but the relationship isn't as strong as in the first group.
So, the scatterplot shows that usually when it's hotter, more coffee is sold. But it's not always the same - sometimes more, sometimes less.