![]() I hope you now clearly see the problem of using percentages with smaller numbers.Ĭoming back to density curves, when you are working with a large distribution you want to have more granular categories. Let me give you an example: a student is extremely excited and tells everyone in his class that he made a 100% improvement in his marks! But what he doesn't say is that his marks went from a 2/30 to 4/30 □. If you use percentages with smaller numbers I often refer to it as lying with statistics – it's a statement that is technically correct but creates the wrong impression in our minds. I also explicitly mentioned that you have a rather large distribution since percentages are often useless for smaller distributions. Well, you might do this for thousands of people, so you are not interested in the exact number – rather the percentage or probability of these categories. You can plot a histogram representing these categories and the number of people whose height falls in each category. So your distribution has let's say 20 categories representing the range of the output (58-59 in, 59-60 in. Say that you need to record the heights of a lot of people. Let's see what I mean through an example. They're simply a way for us to represent a distribution. Let's first talk a bit about density curves, as skewness and kurtosis are based on them. And don't worry – you won't need to know very much math to understand these concepts and learn how to apply them. ![]() In this article, I'll explain two important concepts in statistics: skewness and kurtosis.
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