3. Answer the following concept questions in 1-3 sentences each. (a) Consider the sampling distribution for X. Suppose X, ~ N(75, 25). Do we need the Central Limit Theorem to find P(X < 72) if our sample size is 9? Why or why not. (b) Consider the sampling distribution for X when we have a "large" sample size (n > 30). When we calculate the z-score, why do we divide by o/n instead of o? (c) Consider the Central Limit Theorem for the difference of means. For our standard deviation, we use SD (X1 - X2) : n2

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Please answer part d), e) and f) only.

3. Answer the following concept questions in 1-3 sentences each.
(a) Consider the sampling distribution for X. Suppose X; ~ N(75, 25). Do we need the Central
Limit Theorem to find P(X < 72) if our sample size is 9? Why or why not.
(b) Consider the sampling distribution for X when we have a "large" sample size
(n > 30). When we calculate the z-score, why do we divide by a/Vn instead of o?
(c) Consider the Central Limit Theorem for the difference of means. For our standard deviation,
we use
SD (X1 - X2)
ni
n2
Why don't we want to use
01
02
SD (X1 – X2)
%3D
(d) Consider the Central Limit Theorem for 1 Proportion. Why do we need to check the success
/ failure condition?
(e) Consider the sampling distribution for S°. What assumption about the population do we
need in order to convert S? to a chi-square random variable?
(f) Suppose we want to find P(X < 66). For this particular scenario, we have a small sample
size (n = 20), and the population standard deviation, o, is unknown. We know the sample
standard deviation, s = 9. To perform this calculation, we use the t-distribution. What do
we need to assume about the population to make sure we can use the t-distribution?
(g) The following question was investigated:
If the standard deviation of the mean for the sampling distribution of random
samples of size 64 from a large or infinite population is 5, how large must the
sample size become if the standard deviation is to be reduced to 0.9.
In solving this question, it was determined that n = 1975.308642. Since we cannot talk to
a partial person, how many people do we need to sample?
(h) Suppose you collect data and want to find P(X < some number) by using the t-distribution.
What do we need to assume about the population to make sure we can use the t-distribution?
(i) Suppose we want to solve the following:
Transcribed Image Text:3. Answer the following concept questions in 1-3 sentences each. (a) Consider the sampling distribution for X. Suppose X; ~ N(75, 25). Do we need the Central Limit Theorem to find P(X < 72) if our sample size is 9? Why or why not. (b) Consider the sampling distribution for X when we have a "large" sample size (n > 30). When we calculate the z-score, why do we divide by a/Vn instead of o? (c) Consider the Central Limit Theorem for the difference of means. For our standard deviation, we use SD (X1 - X2) ni n2 Why don't we want to use 01 02 SD (X1 – X2) %3D (d) Consider the Central Limit Theorem for 1 Proportion. Why do we need to check the success / failure condition? (e) Consider the sampling distribution for S°. What assumption about the population do we need in order to convert S? to a chi-square random variable? (f) Suppose we want to find P(X < 66). For this particular scenario, we have a small sample size (n = 20), and the population standard deviation, o, is unknown. We know the sample standard deviation, s = 9. To perform this calculation, we use the t-distribution. What do we need to assume about the population to make sure we can use the t-distribution? (g) The following question was investigated: If the standard deviation of the mean for the sampling distribution of random samples of size 64 from a large or infinite population is 5, how large must the sample size become if the standard deviation is to be reduced to 0.9. In solving this question, it was determined that n = 1975.308642. Since we cannot talk to a partial person, how many people do we need to sample? (h) Suppose you collect data and want to find P(X < some number) by using the t-distribution. What do we need to assume about the population to make sure we can use the t-distribution? (i) Suppose we want to solve the following:
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