You will find Video 2: When Should You Use the Mean and When Should You Use the Median by navigating to: https://mediaplayer.pearsoncmg.com/assets/cWSUSyFyf2fjOGj5lEJQ_w73ZBZdo4JW This video focuses more on when to use a mean and when to use a median. House prices are used to demonstrate that when data are non-symmetric – especially when there are extreme outliers – the median gives a better description of a typical value than the mean. Specifically, the prices of properties on two blocks are compared: in one, all houses are similar and there isn’t much difference between the median and mean; in the other, there is a big expensive block of apartments, so that the mean is nearly twice the median, and far from the cost of any individual property. But we want to get away from the idea that the data, and only the data, drives the choice of descriptive statistic. The example is given that, if you wanted to buy all the houses in Brooklyn, if you took the median, and multiplied by the number of houses, you wouldn’t have enough cash. So the median is a useful descriptive statistic, but the mean is essential for planning and making decisions. Respond to one of the following questions in your initial post: Should you use the median or mean to describe a data set if the data are not skewed? Are the standard deviation or the interquartile range factors? You may read in the newspaper that a study of a new drug for cancer “increased survival by an average of eight weeks.” It turns out that this is a median, and it is used for complicated statistical reasons. But in a perfect world, would you prefer to know the increase in mean or median survival? If the median house price is $1.9m, does that necessarily mean that half of the houses on the block are worth less than $1.9m and half worth more? How do ties figure in?
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