qmb 3200 Exam Study Guide Questions & Answers Latest Updated A+ Gu
Solution
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1. The sampling distribution of is the: probability distribution of all possible values of the same
proportion
2. Doubling the size of the sample will: reduce the standard error of the mean
3. The sample mean is the point estimator of: μ
4. A simple random sample of size n from an infinite population of size N is to
be selected. Each possible sample should have: the same probability of being selected
5. Which of the following statements regarding the sampling distribution is
incorrect?: the standard deviation of the sampling distribution is the standard deviation of the population
6. A simple random sample of size n from an infinite population is a sample
selected such that: each element is selected independently and is selected from the same population
7. The fact that the sampling distribution of sample means can be approximated
by a normal probability distribution whenever the sample size becomes large
is based on the: central limit thereom
8. Cluster sampling is: a probability sampling method
9. The central limit theorem states that: if the sample size n is large, then the sampling distribution
of the sample mean can be approximated by a normal distribution
10. The value of the _____ is used to estimate the value of the population para-
meter: sample statistic
11. Which of the following is not a symbol for the parameter?: S
12. The sample statistic characteristic s is the point estimator of: õ
13. The distribution of values taken by a statistic in all possible samples of the
same size from the same population is called_______.: a sampling distribution
14. Which of the following is a point estimator?: S
15. As a rule of thumb, the sampling distribution of the sample proportion can
be approximated by a normal probability distribution when: n(1-p) > 5 and np >5
16. A sample of 92 observations is taken from an infinite population. The sam-
pling distribution is approximately: normal bc of the central limit theorem
17. The central limit theorem is important in statistics because it enables reason-
ably accurate probabilities to be determined for events involving the sample
average: when the sample size is large regardless of the distribution of the variable
1/2
Solution
Study online at https://quizlet.com/_hpgs3z
1. The sampling distribution of is the: probability distribution of all possible values of the same
proportion
2. Doubling the size of the sample will: reduce the standard error of the mean
3. The sample mean is the point estimator of: μ
4. A simple random sample of size n from an infinite population of size N is to
be selected. Each possible sample should have: the same probability of being selected
5. Which of the following statements regarding the sampling distribution is
incorrect?: the standard deviation of the sampling distribution is the standard deviation of the population
6. A simple random sample of size n from an infinite population is a sample
selected such that: each element is selected independently and is selected from the same population
7. The fact that the sampling distribution of sample means can be approximated
by a normal probability distribution whenever the sample size becomes large
is based on the: central limit thereom
8. Cluster sampling is: a probability sampling method
9. The central limit theorem states that: if the sample size n is large, then the sampling distribution
of the sample mean can be approximated by a normal distribution
10. The value of the _____ is used to estimate the value of the population para-
meter: sample statistic
11. Which of the following is not a symbol for the parameter?: S
12. The sample statistic characteristic s is the point estimator of: õ
13. The distribution of values taken by a statistic in all possible samples of the
same size from the same population is called_______.: a sampling distribution
14. Which of the following is a point estimator?: S
15. As a rule of thumb, the sampling distribution of the sample proportion can
be approximated by a normal probability distribution when: n(1-p) > 5 and np >5
16. A sample of 92 observations is taken from an infinite population. The sam-
pling distribution is approximately: normal bc of the central limit theorem
17. The central limit theorem is important in statistics because it enables reason-
ably accurate probabilities to be determined for events involving the sample
average: when the sample size is large regardless of the distribution of the variable
1/2
