1)Suppose that the population distribution of the gripping strengths of industrial workers is known to have a mean of 110 and standard deviation of 10. For a random sample of 75 workers, what is the probability that the sample mean gripping strength will be
a)Between 109 and 112?
b)Greater than112?
2)On the average, five smokers pass a certain street corners every ten minutes, what is the probability that during a given 10minutes the number of smokers passing will be
A)6 or fewer
B)7 or more
C)Exactly 8
1)
"\\mu = 110 \\\\\n\n\\sigma = 10 \\\\\n\nn = 75 \\\\"
a)
"P(109<X<112) = P(X<112)-P(X<109) \\\\\n\n= P(Z< \\frac{112-110}{10\/ \\sqrt{75}}) -P(Z< \\frac{109-110}{10\/ \\sqrt{75}}) \\\\\n\n= P(Z<1.733)-P(Z< -0.866) \\\\\n\n= 0.9584 -0.1932 \\\\\n\n= 0.7652"
b)
"P(X>112) = 1-P(X<112) \\\\\n\n= 1 -P(Z< \\frac{112-110}{10\/ \\sqrt{75}}) \\\\\n\n= 1 -P(Z<1.733) \\\\\n\n= 1 -0.9584 \\\\\n\n= 0.0416"
2) Assuming that the number of smokers follows Poisson distribution, if X is a Poisson random variable with parameter λ then
"P(X=x) = \\frac{\u03bb^x \\times e^{-\u03bb}}{x!} \\\\\n\n\u03bb = 5"
A) P(X≤6) = P(X=0) + P(X=1) + P(X=2) + P(X=3) + P(X=4) + P(X=5) + P(X=6)
"P(X=0) = \\frac{5^0 \\times e^{-5}}{0!} \\\\\n\n= \\frac{0.006737}{1} \\\\\n\n= 0.006737 \\\\\n\nP(X=1) = \\frac{5^1 \\times e^{-5}}{1!} \\\\\n\n= \\frac{0.03368}{1} \\\\\n\n= 0.03368 \\\\\n\nP(X=2) = \\frac{5^2 \\times e^{-5}}{2!} \\\\\n\n= \\frac{0.16844}{2} \\\\\n\n= 0.08422 \\\\\n\nP(X=3) = \\frac{5^3 \\times e^{-5}}{3!} \\\\\n\n= \\frac{0.84224}{6} \\\\\n\n= 0.14037 \\\\\n\nP(X=4) = \\frac{5^4 \\times e^{-5}}{4!} \\\\\n\n= \\frac{4.21121}{24} \\\\\n\n= 0.17546 \\\\\n\nP(X=5) = \\frac{5^5 \\times e^{-5}}{5!} \\\\\n\n= \\frac{21.056}{120} \\\\\n\n= 0.17546 \\\\\n\nP(X=6) = \\frac{5^6 \\times e^{-5}}{6!} \\\\\n\n= \\frac{105.28}{720} \\\\\n\n= 0.14622 \\\\\n\nP(X\u22646) = P(X=0) + P(X=1) + P(X=2) + P(X=3) + P(X=4) + P(X=5) + P(X=6) \\\\\n\nP(X\u22646) = 0.006737 + 0.03368 + 0.08422 + 0.14037 + 0.17546 + 0.17546 + 0.14622 \\\\\n\n= 0.762447"
B) P(X≥7) = 1 -P(X<7)
P(X<7) = P(≤6)
"P(X\u22646) = 0.762447 \\\\\n\nP(X\u22657) = 1 -0.762447 \\\\\n\n= 0.237553"
C) the probability that, during a given 10-minute period, the number of smokers passing the street corner will be eight is:
"P(X=8) = \\frac{5^8 \\times e^{-5}}{8!} \\\\\n\n= \\frac{2632.01}{40320} \\\\\n\n= 0.065"
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