Question

 

1. The point estimator for the population standard deviation σ  is ___ and the point estimator for the population mean μ is ____.

2. To estimate the value of a population parameter using a sample, we would calculate...

a) a simple random sample, b) a sample statistic, c) a test statistic, d) or both a and b

3. A simple random sample from a finite data set must meet which condition(s)/requirements?

a) you may only sample without replacement; sampling with replacement eliminates the randomness of the sample.

b) each sample selected should include at least 1 observation forma previous sample

c) each sample ( of size n selected from a finite population of size N) should have the same probability of being selected

d) none of the above

4. if the population with which you are working is not normally distributed...

a) you cannot assume the sampling distribution is normally distributed under any circumstances

b) you can assume the sampling distribution is normally distributed if the condition of the Central Limit Theorem is met

c) you can assume the sampling distribution is normally distributed but not by the means described above.

Answer 1

(1)

The point estimator for the population standard deviation is Sample Standard Deviation s and point estimator for the population mean is Sample Mean .

Explanation:By definition, a sample statistic is the characteristic of a sample is a point estimator of population parameter, which is the characteristic of the population. The sample standard deviation (s) is a point estimate of the population standard deviation (). The sample mean () is a point estimate of the population mean ()

(2)

Correct option:

(b) a sample statistic

Explanation: To estimate the population parameter, we first calculate the corresponding sample statistic from the available sample data.

(3)

Correct option:

(c) Each sample (of size n selected from a finite population of size N) should have the same probability of being selected.

Explanation: By definition, a Simple Random Sample (SRS) from finite population of size N is a random sample selected by a method which ensures that all possible samples, of given size n, are equally likely to be chosen.

(4)

Correct option:

(b) you can assume the sampling distribution is normally distributed if the conditions of the Central Limit Theorem is met.

Explanation: By Central Limit Theorem, the sampling distribution of a sample statistic is Normal Distribution irrespective of the shape of the population for large samples,i.e., n > 30.