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Firlakuza [10]
3 years ago
7

Select the correct answer. A number is selected at random from the set {2, 3, 4, ... 10}. Which event, by definition, covers the

entire sample space of this experiment? A. The number is greater than 2. B. The number is not divisible by 5. C. The number is even or less than 12. D. The number is neither prime nor composite. E. The square root of the number is less than 3.
Mathematics
2 answers:
gtnhenbr [62]3 years ago
8 0

Answer:

C. The number is even or less than 12.

Step-by-step explanation:

Let's analyze each event:

A. The number is greater than 2.

This doesn't cover the case when we get number 2. Because 2 is equal to 2, not greater.

B. The number is not divisible by 5.

10 and 5 are divisible by 5, so this doesn't cover the entire sample space.

C. The number is even or less than 12.

Let's notice that every number from {2, 3, 4, ... 10} is less than 12, so the even part of the event doesn't play any role. This covers the entire sample space.

D. The number is neither prime nor composite.

The definition of prime number is exactly the opposite of composite number, so there can't be a number that's neither both. This event doesn't cover any number of the set.

E. The square root of the number is less than 3.

This doesn't cover number 10, because the square root of 10 is approx. 3,16 that's greater than 3.

Stels [109]3 years ago
5 0

Answer:

c

Step-by-step explanation:

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If we compare the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL reject the null hypothesis, so we can say that the population mean is not singificantly higher than 425.  

Step-by-step explanation:

Data given and notation  

\bar X=433.75 represent the mean height for the sample  

\sigma=\sqrt{2500}=50 represent the population standard deviation for the sample  

n=100 sample size  

\mu_o =425 represent the value that we want to test

\alpha=0.01 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)  

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We need to conduct a hypothesis in order to check if the mean height actually is higher than the mean height for men in 1960, the system of hypothesis would be:  

Null hypothesis:\mu \leq 425  

Alternative hypothesis:\mu > 425  

Since we know the population deviation so 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)  

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

z=\frac{433.75-425}{\frac{50}{\sqrt{100}}}=1.75    

P-value

Since is a one right tail test the p value would be:  

p_v =P(z>1.75)=1-P(z  

Conclusion  

If we compare the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL reject the null hypothesis, so we can say that the population mean is not singificantly higher than 425.  

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