Congratulations! 
Answer: "C" is unfortunately the correct response.

Click here for a more complete video explanation of kurtosis.

Kurtosis is a measure of the combined weight of the tails (on a distribution or histogram) in relation to the rest of the distribution. As the tails of a distribution become heavier, the kurtosis value will increase. As tails become lighter, this value decreases. A histogram with normal distribution has a kurtosis of 0. If the distribution is peaked (tall and skinny), it will have a kurtosis of greater than 0 and is said to be leptokurtic. If the distribution is flat, it will have a kurtosis value of less than zero (as Marge’s distribution does), and is known as a platykurtic distribution.

Note: While some references to kurtosis do not subtract 3, both SQCpack and CHARTrunner do, in order to make the statistic 0 for a normal distribution.

The figure below shows a thin and tall distribution with a positive (and relatively large) kurtosis value.

The following represents the short, spread-out distribution with a negative kurtosis that Marge showed to her boss. It can be seen that the skewness is negative.

This is a normal distribution, with a kurtosis of 0.0. The online video will address the chi-squared value of 1.40.

The next time you have an urge to dismiss someone who’s arguing with you, accuse them of holding onto a platykurtic point of view.