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Answer :
[tex][/tex]Given:
population mean, μ =135
population standard deviation, σ = 15
sample size, n = 19
Assume a large population, say > 100,
we can reasonably assume a normal distribution, and a relatively small sample.
The use of the generally simpler formula is justified.
Estimate of sample mean
[tex]\bar{x}=\mu=135[/tex]
Estimate of sample standard deviation
[tex]\s=\sqrt{\frac{\sigma^2}{n}}[/tex]
[tex]=\sqrt{\frac{15^2}{19}}=3.44124[/tex] to 5 decimal places.
Thus, using the normal probability table,
[tex]P(125 [tex]=P(\frac{125-135}{3.44124} [tex]=P(-2.90593 [tex]=P(Z<-2.90593)=0.0018308[/tex]
[tex]=P(Z<-1.45297)=0.0731166[/tex]
Therefore
The probability that the mean weight is between 125 and 130 lbs
P(125 =0.0712858
population mean, μ =135
population standard deviation, σ = 15
sample size, n = 19
Assume a large population, say > 100,
we can reasonably assume a normal distribution, and a relatively small sample.
The use of the generally simpler formula is justified.
Estimate of sample mean
[tex]\bar{x}=\mu=135[/tex]
Estimate of sample standard deviation
[tex]\s=\sqrt{\frac{\sigma^2}{n}}[/tex]
[tex]=\sqrt{\frac{15^2}{19}}=3.44124[/tex] to 5 decimal places.
Thus, using the normal probability table,
[tex]P(125
[tex]=P(Z<-1.45297)=0.0731166[/tex]
Therefore
The probability that the mean weight is between 125 and 130 lbs
P(125
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