You’ve seen how important it is to visualize data sets with histograms, in order to analyze the shape. We want to analyze the shape so that we can think critically about the mean, median and mode to describe the data set. In a skewed distribution, the mean, median and mode differ from each other. And the median might be more useful than the mean in a lot of ways. In a normal distribution The mean, median, and mode are approximately equal. What else is important about knowing the shape of a distribution? Let’s explore this question with a story. I’ve played chess my whole life. I learned when I was four, and started competing in tournaments when I was seven. There are three things I could tell you about my chess abilities. The first is my rating in chess, which all competitive players have, my ratings 1800. Another thing I could tell you, is that among competitive American chess players, I come in 8,110th place, this is base on rating. And the third, is that I rank higher than 88% of American competitive chess players. Which one of these gives you the best sense, of how good I am at chess? For most of you, you won’t know what a rating is, but if you do, pretend like you don’t and you’re hearing this term for the first time. So for the purposes of the quiz, if you knew nothing about chess, What would be the best metric to tell you how good I am?