Use the image to answer the question.
A scatterplot shows the number of cups of coffee sold versus temperature.
The horizontal axis shows temperature, in degrees Fahrenheit, ranging from 0 to 70 in increments of 5, with an initial jump from 0 to 25. The vertical axis shows number of cups of coffee sold, ranging from 0 to 60 in increments of 10. A kink is shown on the horizontal axis close to origin. A tightly packed cluster of data plots is plotted between 30 to 37 on the horizontal axis and 42 to 48 on the vertical axis. A loosely packed cluster of data plots is plotted between 40 to 51 on the horizontal axis 30 and 38 on the vertical axis and. A dot is plotted at 62 on the horizontal axis and 5 on the vertical axis.
Numbers of Cups of Coffee Sold Versus Temperature
Interpret the scatterplot by describing any outliers and patterns of clustering.
(4 points)
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.
From the scatterplot, we can observe a few outliers and patterns of clustering.
Firstly, there is a noticeable outlier represented by a dot plotted at 62 on the horizontal axis and 5 on the vertical axis. This outlier suggests that at higher temperatures, there is an unexpectedly low number of cups of coffee sold.
In terms of clustering, we can see two distinct clusters of data plots. The first cluster is tightly packed and is located between 30 to 37 on the horizontal axis and 42 to 48 on the vertical axis. This suggests that at temperatures within this range, there is a consistent and high number of cups of coffee sold.
The second cluster is loosely packed and spans from 40 to 51 on the horizontal axis and 30 to 38 on the vertical axis. This implies that at temperatures within this range, the number of cups of coffee sold varies more widely, with some outliers being observed.
Overall, the scatterplot indicates that there is a relationship between temperature and the number of cups of coffee sold, with the presence of some outliers and noticeable patterns of clustering.
To interpret the scatterplot and identify any outliers and patterns of clustering, we examine the distribution of the data points.
First, we look for outliers, which are data points that deviate significantly from the overall pattern. In this scatterplot, there is one dot plotted at 62 on the horizontal axis and 5 on the vertical axis. This data point is an outlier since it is far away from the main cluster of points.
Next, we look for patterns of clustering. In this scatterplot, we observe two distinct clusters of data points. The first cluster is tightly packed and is plotted between approximately 30 to 37 on the horizontal axis and 42 to 48 on the vertical axis. The second cluster is loosely packed and is plotted between approximately 40 to 51 on the horizontal axis and 30 to 38 on the vertical axis. These clusters indicate that there may be a relationship between the temperature and the number of cups of coffee sold.
To summarize, the scatterplot shows one outlier at 62 on the horizontal axis and 5 on the vertical axis, indicating an unusual data point. Additionally, there are two clusters of data points, suggesting a potential relationship between temperature and the number of cups of coffee sold.