to illustrate differences in shape for different normal distributions
I think that because we draw all of our normal curves with the same size and shape, we forget that they are not really all the same - the mean and standard deviation of different normal distributions actually affects how they look. A larger standard deviation, for example, actually makes the curve flatter because it has greater spread - and the location of the mean results in a shift either to the left or to the right of the entire curve.
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We take a look at the actual difference in size and shape between a standard normal curve (mean 0, standard deviation 1) and a normal curve for IQ scores (mean 100, standard deviation 15). With the curves drawn to perspective, you can get a better understanding of the "area under the curve" concept.
