Americans ate an average of 25.7 pounds of confectionery products each last year and
spent an average of $61.50 per person doing so. If the standard deviation of consumption is 3.75 pounds and the standard deviation of the amount spent is %5.89, find the following:
a. The probability that the sample mean confectionary consumption for a random sample
of 40 American consumers was greater than 27 pounds.
b. The probability that for a random sample of 50, the sample mean for confectionary
spending exceeded $60.00
Solution:
Let's denote given values:
"\\mu1=25.7pounds;"
"\\mu2=61.5" $;
"\\sigma1=3.75pounds;"
"X1=27pounds" -sample value for a);
"X2=60" $ - sample values for b);
"\\sigma2=5.89" $;
"N1=40" - sample size for a);
"N2=50" - sample size for b);
We need to find z-scores:
"z=\\frac{X-\\mu}{\\sigma_e};" here "\\sigma_e=\\frac{\\sigma}{\\sqrt{N}}" - standard deviation error when N sample numbers;
So,
a) "z1=\\frac{X1-\\mu1}{\\sigma_e1};" "\\sigma_{e1}=\\frac{\\sigma1}{\\sqrt{N1}}=\\frac{3.75}{\\sqrt{40}}=0.59293;"
"z1=\\frac{27-25.7}{0.59293}=2.19;"
Now, we need to check z-table, which "P=0.9857" for "z1=2.19."
If we want to find greater then 27 pounds, so
"P1=1-P=1-0.9857=0.0143;" or "P1=1.43" %.
b) "z2=\\frac{X2-\\mu2}{\\sigma_e2};" "\\sigma_{e2}=\\frac{\\sigma2}{\\sqrt{N2}}=\\frac{5.89}{\\sqrt{50}}=0.833;"
"z2=\\frac{60-61.5}{0.833}=-1.8;"
"P=0.0359" for "z2=-1.8."
If we want to find greater than 60$, so
"P2=1-P=1-0.0358=0.9641;" or "P2=96.41" %.
Answer:
a) "P1=1.43" %.
b) "P2=96.41" %.
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