A food company sells salmon to various customers. The mean weight of the salmon is 37 lb with a standard deviation of 2 lbs. The company ships them to restaurants in boxes of 9 ​salmon, to grocery stores in cartons of 49 ​salmon, and to discount outlet stores in pallets of 64 salmon. To forecast​ costs, the shipping department needs to estimate the standard deviation of the mean weight of the salmon in each type of shipment.

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Answer:

The standard deviation for the mean weigth of Salmon is 2/3 lbs for restaurants, 2/7 lbs for grocery stores and 1/4 lbs for discount order stores.

Step-by-step explanation:

The mean sample of the sum of n random variables is

[tex]\overline{X} = \frac{X_1+X_2+...+X_n}{n}[/tex]

If [tex] X_1, ..., X_n [/tex] are indentically distributed and independent, like in the situation of the problem, then the variance of [tex] X_1 + .... + X_n [/tex] will be the sum of the variances, in other words, it will be n times the variance of [tex] X_1 [/tex] .

However if we multiply this mean by 1/n (in other words, divide by n), then we have to divide the variance by 1/n², thus [tex] \overkine{X} = \frac{V(X_1)}{n} [/tex] and as a result, the standard deviation of [tex] \overline{X} [/tex] is the standard deviation of [tex] X_1 [/tex] divided by [tex] \sqrt{n} [/tex] .

Since the standard deviation of the weigth of a Salmon is 2 lbs, then the standard deviations for the mean weigth will be:

  • Restaurants: We have boxes with 9 salmon each, so it will be [tex] \frac{2}{\sqrt{9}} = \frac{2}{3}[/tex]
  • Grocery stores: Each carton has 49 salmon, thus the standard deviation is [tex] \frac{2}{\sqrt{49}} = \frac{2}{7}[/tex]
  • Discount outlet stores: Each pallet has 64 salmon, as a result, the standard deviation is [tex] \frac{2}{\sqrt{64}} = \frac{1}{4} [/tex]

We conclude that de standard deivation of the mean weigth of salmon of the types of shipment given is: 2/3 lbs for restaurants, 2/7 lbs for grocery stores and 1/4 lbs for discount outlet stores.

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