In a scatterplot of number of cups of coffee sold versus temperature, outliers may indicate unusual or unexpected data points that do not align with the overall trend of the data.
If there are outliers present, they could represent days where the number of cups of coffee sold deviates significantly from the usual pattern, possibly due to external factors such as a special event or promotion.
Patterns of clustering in the scatterplot can show how the number of cups of coffee sold tends to vary with temperature. For example, if there is a clear upward trend in the data points, with the number of cups of coffee sold increasing as temperature rises, this indicates a positive correlation between the two variables. On the other hand, if the data points are spread out and do not show a clear trend, this suggests a weak or no correlation between the number of cups of coffee sold and temperature.
Overall, analyzing the scatterplot can provide insights into how temperature affects the number of cups of coffee sold and can help identify any influential outliers in the data.
Scatterplots and data analysis unit test number of cups of coffee versus temperature
Numbers of cups of coffee, sold versus temperature, interpret the scatterplot by describing any outliers and patterns of clustering
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