A news article estimated that only 4% of those age 65 and older who prefer to watch the news, rather than to read or listen, watch the news online. This estimate was based on a survey of a large sample of adult Americans. Consider the population consisting of all adult Americans age 65 and older who prefer to watch the news, and suppose that for this population the actual proportion who prefer to watch online is 0.04. (a) A random sample of n = 100 people will be selected from this population and p, the proportion of people who prefer to watch online, will be calculated. What are the mean and standard deviation of the sampling distribution of p? (Round your standard deviation to four decimal places.) mean 0.04 standard deviation 0.0196 (b) Is the sampling distribution of p approximately normal for random samples of size n = 100? Explain. The sampling distribution of p is approximately normal because np is less than 10. O The sampling distribution of p is approximately normal because np is at least 10. The sampling distribution of p is not approximately normal because np is less than 10. The sampling distribution of p is not approximately normal because np is at least 10. The sampling distribution of is not approximately normal because n(1-P) is less than 10. (c) Suppose that the sample size is n = 400 rather than n = 100. What are the values for the mean and standard deviation when n = 400? (Round your standard deviation to four decimal places.) mean 0.03 standard deviation 0.0085 Does the change in sample size affect the mean and standard deviation of the sampling distribution of ? If not, explain why not. (Select all that apply.) 2 When the sample size increases, the mean increases. When the sample size increases, the mean decreases. When the sample size increases, the mean stays the same. The sampling distribution is always centered at the population mean, regardless of sample size. When the sample size increases, the standard deviation increases. When the sample size increases, the standard deviation decreases When the sample size increase the standard deviation stays the same. The standard deviation of the sampling distribution is always the same as the standard deviation of the population distribution regardless of sample size. Suppose that the sample size is n = 400 rather than n = 100. What are the values for the mean and standard deviation when n = 400? (Round your standard deviation to four decimal places.) mean 0.03 standard deviation 0.0085 Does the change in sample size affect the mean and standard deviation of the sampling distribution of p? If not, explain why not. (Select all that apply.) When the sample size increases, the mean increases. When the sample size increases, the mean decreases. When the sample size increases, the mean stays the same. The sampling distribution is always centered at the population mean, regardless of sample size. When the sample size increases, the standard deviation increases. When the sample size increases, the standard deviation decreases. When the sample size increases, the standard deviation stays the same. The standard deviation of the sampling distribution is always the same as the standard deviation of the population distribution, regardless of sample size. (d) is the sampling distribution of p approximately normal for random samples of size n = 400? Explain. The sampling distribution of p is approximately normal because np and n(1 - p) are both at least 10. The sampling distribution of p is approximately normal because np and n(1 - 0) are both less than 10. The sampling distribution of p is not approximately normal because np and n(i - p) are both at least 10. • The sampling distribution of p is not approximately normal because np and n(1-P) are both less than 10. The sampling distribution of p is not approximately normal because only np is at least 10.

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Answer:

(a) The mean is 0.04

The standard deviation is approximately 0.0196

(b) The sampling distribution of p is not approximately normal because n·p is less than 10

(c) Given that n  = 400, we have;

i) The mean is 0.04

The standard deviation is approximately 0.0098

ii) The sampling distribution is always centered at the population mean, regardless of the sample size

iii) When the sample size increases, the standard deviation decreases

(d) The sampling distribution of p is approximately normal because n·p and n·(1 - p) are both at least 10

Step-by-step explanation:

(a) From the question, we have that the actual proportion of all adult Americans who watch online = 0.04

Given that the sample size, 'n' is 100 which is larger than 30, we can assume that the distribution of the sample mean is normal

Therefore, the mean (proportion) of the sample, P = The mean (proportion) of the population = 0.04

The mean, P = 0.04

The standard deviation, σ = √((p·(1 - p))/n)

∴ σ = √((0.04·(1 - 0.04))/100) ≈ 0.0196

(b) The sampling of p is approximately normal, given that the sample size, 'n' = 100 which is randomly selected from the population, we have;

The sampling distribution = n·p  = 100 × 0.04 = 4 <10

Therefore, the sample is not approximately normal because the sampling distribution, n·p = 4 which is less than 10

c) Given that n  = 400, we have;

p = 0.04 = The [population mean

The standard deviation, σ √((0.04·(1 - 0.04))/400) ≈ 0.0098

According to the central limit theorem when the sample size increases, the mean approaches the population mean, therefore, the sampling distribution is always centered at the population mean, regardless of the sample size

When the sample size increases, the standard deviation decreases

(d) Given that when the sample size, n = 400, we have;

n·p = 400 × 0.04 = 16 > 10

Similarly, we have;

n·(1 - p) = 400 × (1 - 0.04) = 384 > 10

The sample is approximately normal

Therefore, the sampling distribution of p is approximately normal because np and n(1 - p) are both at least 10