Vol. 6, No. 10
For several months, Marge Orrine has been hitting a blank wall in her quest for Black Belt status in her company. If learning comes through failures, Marge could be close to a Ph.D. in statistics, for she has indeed learned a great deal about central location and variability. Learning basic descriptive statistics by running into walls is not, perhaps, the most efficient path to education, but Marge Orrine forges ahead nonetheless.
With the weight of each stick of butter that National Dairy Products produces as her primary focus, Marge is challenged by the wide ranges among these weights. Using CHARTrunner to create a histogram, she shows the chart to her boss, Miles Aweigh, with the observation that the standard deviation appears to be 1.82
“What’s responsible for this kurtosis of –1.1?” her boss asks.
“That’s nothing to worry about,” Marge responds confidently. “In fact, it’s a good sign, since a larger kurtosis value would be responsible for predictable package weights, since it indicates a small amount of variation in the weights.”
Is Marge’s stab in the dark anywhere close to explaining the negative kurtosis?
2004 PQ Systems.
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