What is the least common denominator of 8 and 12
1 answer:
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Answer:
(a) P(X > $57,000) = 0.0643
(b) P(X < $46,000) = 0.1423
(c) P(X > $40,000) = 0.0066
(d) P($45,000 < X < $54,000) = 0.6959
Step-by-step explanation:
We are given that U.S. Bureau of Economic Statistics reports that the average annual salary in the metropolitan Boston area is $50,542.
Suppose annual salaries in the metropolitan Boston area are normally distributed with a standard deviation of $4,246.
<em>Let X = annual salaries in the metropolitan Boston area</em>
SO, X ~ Normal()
The z-score probability distribution for normal distribution is given by;
Z = ~ N(0,1)
where, = average annual salary in the Boston area = $50,542
= standard deviation = $4,246
(a) Probability that the worker’s annual salary is more than $57,000 is given by = P(X > $57,000)
P(X > $57,000) = P( >
) = P(Z > 1.52) = 1 - P(Z
1.52)
= 1 - 0.93574 = <u>0.0643</u>
<em>The above probability is calculated by looking at the value of x = 1.52 in the z table which gave an area of 0.93574</em>.
(b) Probability that the worker’s annual salary is less than $46,000 is given by = P(X < $46,000)
P(X < $46,000) = P( <
) = P(Z < -1.07) = 1 - P(Z
1.07)
= 1 - 0.85769 = <u>0.1423</u>
<em>The above probability is calculated by looking at the value of x = 1.07 in the z table which gave an area of 0.85769</em>.
(c) Probability that the worker’s annual salary is more than $40,000 is given by = P(X > $40,000)
P(X > $40,000) = P( >
) = P(Z > -2.48) = P(Z < 2.48)
= 1 - 0.99343 = <u>0.0066</u>
<em>The above probability is calculated by looking at the value of x = 2.48 in the z table which gave an area of 0.99343</em>.
(d) Probability that the worker’s annual salary is between $45,000 and $54,000 is given by = P($45,000 < X < $54,000)
P($45,000 < X < $54,000) = P(X < $54,000) - P(X $45,000)
P(X < $54,000) = P( <
) = P(Z < 0.81) = 0.79103
P(X $45,000) = P(
) = P(Z
-1.31) = 1 - P(Z < 1.31)
= 1 - 0.90490 = 0.0951
<em>The above probability is calculated by looking at the value of x = 0.81 and x = 1.31 in the z table which gave an area of 0.79103 and 0.9049 respectively</em>.
Therefore, P($45,000 < X < $54,000) = 0.79103 - 0.0951 = <u>0.6959</u>
Answer:
The optimal production quantity is 9,322 cards.
Step-by-step explanation:
The information provided is:
Cost of the paper = $0.05 per card
Cost of printing = $0.15 per card
Selling price = $2.15 per card
Number of region (n) = 4
Mean demand = 2000
Standard deviation = 500
Compute the total cost per card as follows:
Total cost per card = Cost of the paper + Cost of printing
= $0.05 + $0.15
= $0.20
Compute the total demand as follows:
Total demand = Mean × n
= 2000 × 4
= 8000
Compute the standard deviation of total demand as follows:
Compute the profit earned per card as follows:
Profit = Selling Price - Total Cost Price
= $2.15 - $0.20
= $1.95
The loss incurred per card is:
Loss = Total Cost Price = $0.20
Compute the optimal probability as follows:
Use Excel's NORMSINV{0.907} function to find the Z-score.
<em>z</em> = 1.322
Compute the optimal production quantity for the card as follows:
Thus, the optimal production quantity is 9,322 cards.