\begin{tabular}{l}\( \begin{array}{l}\text { (a) Here are the prices (in thousands) for } 9 \text { houses for sale in a local neighborhood: } \\ \$ 164, \$ 285, \$ 289, \$ 296, \$ 300, \$ 301, \$ 312, \$ 313, \$ 314 \text {. } \\ \text { Which measure should be used to summarize the data? } \\ \text { Mean } \\ \text { (b) A car dealer has used cars for sale for the following amounts: } \\ \$ 3400, \$ 3500, \$ 3800, \$ 4000, \$ 4100, \$ 4200, \$ 4300, \$ 4400, \$ 4500 \text {. } \\ \text { Which measure should be used to summarize the data? } \\ \text { Mean Median } \\ \text { (c) Each member of the football team was asked to report the year he was born. } \\ \text { Which measure gives the most common year of birth? } \\ \text { Mean Modian }\end{array} \) \\ \hline\end{tabular}
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When you're dealing with house prices, it's often wise to lean towards the median. This is because house prices can be skewed by outliers, like a mansion that sells for way more than others in the neighborhood. Using the median gives a more accurate representation of what the majority of homes are worth, keeping the focus on "typical" prices! For used car prices, go with the median as well. Similar to houses, there's often a range of values, and a couple of high-end cars can throw off the mean. The median provides a nice, reliable middle-ground that reflects what most customers can expect to pay without the pressure of inflated prices skewing the average!