Question #107503
Restaurant “King Steak” offers a set lunch of a 150 grams steak for $100. The steaks are cut by a machine
and the weight of a steak can be assumed to be normally distributed with mean 152 grams and standard
deviation 1.7 grams.
(a) What is the probability that a customer gets a steak that weighs less than 150 grams?
(b) There is a 4% chance that a customer gets a steak that weighs less than W grams. What is the value of
W?
(c) There is a table with 8 customers, everyone orders this set lunch. What is the probability that there are
exactly 2 customers whose steaks weigh less than 150 grams?
(d) Sometimes there are customers ordering two sets of lunch. Use T to denote the total weight of two
steaks. Find the mean, variance, and standard deviation of T.
1
Expert's answer
2020-04-02T12:54:25-0400

Let X=X= the weight of a steak:X(N,σ2)X\sim (N, \sigma^2)

Then Z=XμσN(0,1)Z=\dfrac{X-\mu}{\sigma}\sim N(0,1)

Given that μ=152 g,σ=1.7 g\mu=152\ g, \sigma=1.7\ g

(a) What is the probability that a customer gets a steak that weighs less than 150 grams? 


P(X<150)=P(Z<1501521.7)P(X<150)=P(Z<{150-152\over 1.7})\approxP(Z<1.17647)0.1197\approx P(Z<-1.17647)\approx0.1197

(b) There is a 4% chance that a customer gets a steak that weighs less than W grams. What is the value of W? 


P(X<W)=P(Z<W1521.7)=0.04P(X<W)=P(Z<{W-152\over 1.7})=0.04

W1521.71.7507{W-152\over 1.7}\approx-1.7507

W149 gW\approx149\ g

(c) There is a table with 8 customers, everyone orders this set lunch. What is the probability that there are exactly 2 customers whose steaks weigh less than 150 grams? 

Let Y=Y= the number of customers whose steaks weigh less than 150 grams: YBin(n,p)Y\sim Bin (n,p)


P(Y=y)=(ny)py(1p)nyP(Y=y)=\binom{n}{y}p^y(1-p)^{n-y}

Given that n=8,p=0.1197n=8, p=0.1197


P(Y=2)=(82)(0.1197)2(10.1197)820.1867P(Y=2)=\binom{8}{2}(0.1197)^2(1-0.1197)^{8-2}\approx0.1867

(d) Sometimes there are customers ordering two sets of lunch. Use T to denote the total weight of two

steaks. Find the mean, variance, and standard deviation of T.


TN(μ+μ,σ2+σ2)T\sim N(\mu+\mu,\sigma^2+\sigma^2)

Then


μT=150 g+150 g=300 g\mu_T=150\ g+150\ g=300\ g

Var(T)=σT2=1.72+1.72=5.78Var(T)=\sigma_T^2=1.7^2+1.7^2=5.78

σT=5.78 g=1.72 g2.4 g\sigma_T=\sqrt{5.78}\ g=1.7\sqrt{2}\ g\approx2.4\ g


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