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aemi2012 · Sep 12, 2012, 03:55 PM

Gobblers firm presently has demographic data on all 5,000 of its male customers. It has found that the average weight of all its male customers is 195 lbs with a standard deviation of 20 lb. In addition, the average weight has been found to be normally distributed.

4. gobbler has conducted some analysis that reveals that approximately 5% of its customers have an average weight below 160 lb. based on this info, in a randomly drawn sample of 1,000 customers, what % of customers could be expected to have an average weight below 160?

6. based upon the population data (mean=195, standard deviation=20) what is the weight value that you would expect only 25% of the customers to exceed?
I got x=208.48. I used 75%=.674 and solved for the X.

7. Based upon the population data (mean=195, standard deviation=20) what is the weight level that would expect 90% of the customers to exceed?
I used 90%=1.282 and solved for the X and got X=220.64.
220.64 is 25.64 from the mean 195. Than I did 195-25.64 and got 169.36. Is this correct?

9. Gobblers has conducted some analysis in consideration of producing only certain sizes of pants as few customers weigh less 135 lb. nor more than 225. If Gobblers is considering a minimum pants size that would fit an average man of 140 lb. how many of its customers would be expected to have a weight below this value? (average weight=195, standard deviation=20)

10. If gobblers chose to model the distribution of customer weights with the discrete distribution shown below, what is the probability of a customer having a weight 215lb. Or less?

Weight %of customers
100lb -135lb .13%
135 - 155 2.15%
155-175 13.59%
175-195 34.13%
195-215 34.13%
215-235 13.59%
235-255 2.15%
255lb or more .13%
I added the % that shows weight less than or equal to and got 97.72%. Is this answer correct?

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