To determine the most appropriate measure of center for the football team's total points, we first need to consider the presence of outliers in the data.
In this case, if there is an outlier of 63 (assuming that is significantly higher than the other data points) and possibly also a mention of an outlier as 20 (if it is significantly lower), then the distribution may be skewed.
Here's a breakdown of the options based on the information provided:
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Mean because there are no outliers: This option is not appropriate if there are indeed outliers, as the mean can be heavily influenced by extreme values, leading to a misleading representation of the data.
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Median due to outlier of 63: The median is a better measure of center when dealing with outliers, as it is not affected by extreme values. This makes it a suitable choice if there are significant outliers.
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Range because there is no outlier: The range simply provides the difference between the maximum and minimum values and does not offer a measure of center.
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Interquartile range due to the outlier of 20: While the interquartile range (IQR) can provide insight into variability, it is not a measure of center.
Given these considerations, the best response would be:
Median due to outlier of 63.
This is because the median will provide a more accurate measure of center when outliers are present.