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sertanlavr [38]
4 years ago
7

Find the appropriate rejection regions for the large-sample test statistic z in these cases. (Round your answers to two decimal

places. If the test is one-tailed, enter NONE for the unused region.)(a) A right-tailed test with α=0.01z >z <(b) A two-tailed test at the 5% significance levelz > _z < _
Mathematics
1 answer:
Usimov [2.4K]4 years ago
7 0

Answer:

a) We have that the significance is given by \alpha =0.01 and we know that we have a right tailed test.

So for this case we need to look in the normal standard dsitribution a critical value that accumulates 1% of the area on the right and 99% of the area on the left. This value can be founded with the following excel code:

"=NORM.INV(1-0.01,0,1)"

And we got for this case z_{crit}=2.33

So then the rejection region would be z>2.33

b) We have that the significance is given by \alpha =0.05, \alpha/2 =0.025 and we know that we have a two tailed test.

So for this case we need to look in the normal standard dsitribution a critical value that accumulates 2.5% of the area on the right and 97.5% of the area on the left. This value can be founded with the following excel code:

"=NORM.INV(1-0.025,0,1)"

And we got for this case z_{crit}=\pm 1.96

So then the rejection region would be z>1.96 \cup z

Step-by-step explanation:

Part a

We have that the significance is given by \alpha =0.01 and we know that we have a right tailed test.

So for this case we need to look in the normal standard dsitribution a critical value that accumulates 1% of the area on the right and 99% of the area on the left. This value can be founded with the following excel code:

"=NORM.INV(1-0.01,0,1)"

And we got for this case z_{crit}=2.33

So then the rejection region would be z>2.33

Part b

We have that the significance is given by \alpha =0.05, \alpha/2 =0.025 and we know that we have a two tailed test.

So for this case we need to look in the normal standard dsitribution a critical value that accumulates 2.5% of the area on the right and 97.5% of the area on the left. This value can be founded with the following excel code:

"=NORM.INV(1-0.025,0,1)"

And we got for this case z_{crit}=\pm 1.96

So then the rejection region would be z>1.96 \cup z

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The HCF is 75

Step-by-step explanation:

Here, we want to get the highest common factors of the two numbers

To do this, we have to write the numbers as the product of their prime factors

We have;

3,000 = 2 * 2 * 2 * 3 * 5 * 5 * 5

525 = 3 * 5 * 5 * 7

now looking at this, we can see that in both numbers, we can have 3 * 5 * 5 taken out as it is common to both numbers

This represents the highest common factor of the two numbers

and that is 75

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Answer:

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Step-by-step explanation:

<u><em>Step:-1</em></u>

Given that the size of the sample 'n' =12

Given that mean of the sample x⁻ = 1.0 pounds

Given that the standard deviation of the sample (S) = 0.65 pounds

<u><em>Step:- 2</em></u>

<em>The 95% confidence interval for the mean waste recycled per person per day for the population of Montana.</em>

<em />(x^{-} - t_{0.05} \frac{S.D}{\sqrt{n} } , x^{-} + t_{0.05} \frac{S.D}{\sqrt{n} } )<em />

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<u><em>Final answer:-</em></u>

<em>The 95% confidence interval for the mean waste recycled per person per day for the population of Montana.</em>

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<u><em /></u>

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