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The mean is one of the most common measures of central tendency used in statistics. It helps to summarize a data set with a single value representing the average. To calculate the mean, you first need to add up all the numbers in the data set. For the given data set, the sum of the numbers is 35. Then, divide this sum by the total number of values in the data set. Since there are 12 numbers in our data, the mean is calculated as follows: \[ \text{Mean} = \frac{35}{12} \approx 2.92 \] This value tells us that, on average, there were about 2.92 power outages per month in Oak City. Calculating the mean gives you a quick snapshot of the general trend in the data, but it doesn't provide information about the distribution or spread of other data points.

The median is another crucial measure of central tendency and tells us the middle value of an ordered data set. Finding the median requires first arranging the data set from least to greatest. In the data provided, the ordered set is:0, 1, 2, 2, 2, 2, 3, 3, 4, 4, 5, 7. For an even number of observations, the median is the average of the two middle numbers. Here, the middle values are 2 and 3. Therefore, the median is calculated as: \[ \text{Median} = \frac{(2+3)}{2} = 2.5 \] The median gives us insight into the central point of the data split into two halves, showing us that half of the months had 2 or fewer outages, while the other half had more.

The mode of a data set is the number that appears most frequently. In situations where some numbers repeat more often than others, the mode can highlight the most common occurrence within the data. After organizing the data set, we observe that the number 2 appears four times, which is more frequent than any other number. Thus, the mode of this data set is 2. The mode is particularly useful for understanding the most typical case in your data set, giving a sense of where most observations tend to occur. In this scenario, having a mode of 2 indicates that the town of Oak City most commonly experiences two outages per month.