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tatiyna
2 years ago
13

A large but sparsely populated county has two small hospitals, one at the south end of the county and the other at the north end

. The souths hospital’s emergency room has four beds, whereas the north hospital’s emergency room has only three beds. Let X denote the number of south beds occupied at a particular time on a given day, and let Y denote the number of north beds occupied at the same time on the same day. Suppose that these two rv’s are independent; that the pmf of X puts probability masses 0.1, 0.2, 0.3, 0.2, and 0.2 on the x values 0, 1, 2, 3, and 4 respectively; and that the pmf of Y distributes probabilities 0.1, 0.3, 0.4, and 0.2 on the y values 0, 1, 2, and 3 respectively.
a. Display the joint pmf of X and Y in a joint probability table.
b. Compute P(X # 1 and Y # 1) by adding probabilities from the joint pmf, and verify that this equals the product of P(X # 1) and P(Y # 1).
c. Express the event that the total number of beds occupied at the two hospitals combined is at most 1 in terms of X and Y, and then calculate this probability.
d. What is the probability that at least one of the two hospitals has no beds occupied?
Mathematics
1 answer:
Inessa05 [86]2 years ago
6 0
D- what is the probability that Lear one of the 2 hospitals has no beds occupied
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Alternative hypothesis:p_{1} > p_{2}  

z=3.02  

p_v =P(Z>3.02)=0.00127  

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Step-by-step explanation:

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X_{1}=0.86*1004 represent the number of Canadians randomly sampled by Gallup that read at least one book in the past year

X_{2}=0.81*1009 represent the number of Britons randomly sampled that read at least one book in the past year

n_{1}=1004 sample of Gallup selected

n_{2}=1009 sample of Britons selected

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p_{2}=0.81 represent the proportion of Britons randomly sampled that read at least one book in the past year

z would represent the statistic (variable of interest)  

p_v represent the value for the test (variable of interest)

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the proportion for men with red/green color blindness is a higher than the rate for women  , the system of hypothesis would be:  

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Alternative hypothesis:p_{1} > p_{2}  

We need to apply a z test to compare proportions, and the statistic is given by:  

z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}   (1)

Where \hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{0.81+0.86}{2}=0.835

3) Calculate the statistic

Replacing in formula (1) the values obtained we got this:  

z=\frac{0.86-0.81}{\sqrt{0.835(1-0.835)(\frac{1}{1004}+\frac{1}{1009})}}=3.02  

4) Statistical decision

For this case we don't have a significance level provided \alpha, but we can calculate the p value for this test.  

Since is a one side test the p value would be:  

p_v =P(Z>3.02)=0.00127  

So the p value is a very low value and using any significance level for example \alpha=0.05, 0,1,0.15 always p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion of Canadians is not significantly higher than the porportions of readers at Britons.  

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Step-by-step explanation:

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