A manufacturer of power tools claims that the average amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The probability that the sample mean will be greater than 88 minutes is __________. What type of problem is this?
Poisson
Random variable
Sample mean
Sample proportion
Normal
MEAN= 80 MINUTES AND S.D= 40 MINUTES
n=64
sample mean will be 80 minutes and S.D(= 40/sqrt(64)= 40/8=5
P ( X>88 )=P ( X−μ>88−80 )=P ((X−μ)/σ>(88−80)/5)
Since Z=(x−μ)/σ and (88−80)/5=1.6 we have:
P ( X>88 )=P ( Z>1.6 )
Use the standard normal table to conclude that:
P (Z>1.6)=0.0548
This problem is NORMAL. But actually it is sampling distribution problem.
A manufacturer of power tools claims that the average amount of time required to assemble their...
A manufacturer of power tools claims that the average amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The probability that the sample mean will be greater than 88 minutes is __________. What type of problem is this? Poisson Random variable Sample mean Sample proportion Normal
A manufacturer of power tools claims that the average amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The probability that the sample mean will be greater than 88 minutes is __________. Which parameters in the problem do the data values (80, 40, 64, 88) represent?
A manufacturer of power tools claims that the average amount of time required to assemble their top-of-the-line table saw is 80 minutes with a standard deviation of 40 minutes. Suppose a random sample of 64 purchasers of this table saw is taken. The probability that the sample mean will be greater than 88 minutes is __________. You should use the finite population correction factor for this problem. True False
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