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jeka57 [31]
3 years ago
10

The entertainment sports industry employs athletes, coaches, referees, and related workers. Of these, 0.35 work part time and 0.

52 earn more than $20,540 annually. If 0.3 of these employees work full time and earn more than $20,540, what proportion of the industry's employees are full time or earn more than $20,540
Mathematics
1 answer:
Alona [7]3 years ago
7 0
<h2>0.87</h2>

Step-by-step explanation:

let A be the event that employees work full time

Pr(A) =  1 - 0.35=  0.65   (  given : Pr( employee work part time) = 0.35)

let B be the event that employees earn more than $20,540

Pr(B) =  0.52

Pr(  employee work full time and earn more than $20,540) =  0.3

Pr( A∩B) = 0.3

we know that

Pr( employee work full time or earn more than $20,540) = Pr( A∪B)

Also

Pr( A∪B)   =  Pr(A)  + Pr(B)  -  Pr(A∩B)

                   =  0.65   + 0.52  -   0.3

                    =    1.17    -   0.30

                     =    0.87

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k/11 = 7

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K is being divided by 11 and equals 7

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Suppose the standard deviation of a normal population is known to be 3, and H0 asserts that the mean is equal to 12. A random sa
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Answer:

z=\frac{12.95-12}{\frac{3}{\sqrt{36}}}=1.9  

p_v =P(z>1.9)=0.0287  

If we compare the p value and the significance level given \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is higher than 12 at 5% of signficance.  

Step-by-step explanation:

Data given and notation  

\bar X=12.95 represent the sample mean

\sigma=3 represent the population standard deviation for the sample  

n=36 sample size  

\mu_o =12 represent the value that we want to test  

\alpha=0.05 represent the significance level for the hypothesis test.  

z would represent the statistic (variable of interest)  

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

State the null and alternative hypotheses.  

We need to conduct a hypothesis in order to check if the mean is equal to 12, the system of hypothesis would be:  

Null hypothesis:\mu \leq 12  

Alternative hypothesis:\mu > 12  

Since we know the population deviation, is better apply a z test to compare the actual mean to the reference value, and the statistic is given by:  

z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}} (1)  

z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Calculate the statistic  

We can replace in formula (1) the info given like this:  

z=\frac{12.95-12}{\frac{3}{\sqrt{36}}}=1.9  

P-value  

Since is a right tailed test the p value would be:  

p_v =P(z>1.9)=0.0287  

Conclusion  

If we compare the p value and the significance level given \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is higher than 12 at 5% of signficance.  

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Total = 16
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