To determine the best measure of center for the given dataset {0.06, 1, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 9}, let's evaluate the different options:
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Mean: This is calculated by summing all the numbers and dividing by the count of numbers. \[ \text{Mean} = \frac{0.06 + 1 + 1 + 2 + 3 + 4 + 4 + 5 + 6 + 7 + 8 + 9 + 9}{13} = \frac{60.06}{13} \approx 4.62 \]
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Median: To find the median, we need to arrange the numbers in order (which they already are) and find the middle value. Since there are 13 numbers (an odd count), the median is the value in the 7th position. \[ \text{Median} = 5 \]
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Mode: The mode is the value that appears most frequently. In this dataset, both 1 and 4 appear twice, while all other values appear once. Thus, we have two modes (bimodal): 1 and 4.
Considering the measures of central tendency:
- The mean is affected by the outlier (0.06), which pulls it down compared to the median.
- The median (5) is a better representation of the center, as it is less affected by outliers.
- The mode, in this case, is also informative but not necessarily the best representation for a typical value, especially since we have two of them.
Given the skewness due to the outlier 0.06, the median is the best measure of center for this dataset. Therefore, the response is:
median.