Author Question: Which of the following is true about sample size? a. An adequate sample size is particularly ... (Read 52 times)

olgavictoria · **on:** Jul 8, 2018

Which of the following is true about sample size?

a. An adequate sample size is particularly important to detect differences when they do in fact exist.
b. Evaluating the possibility of a Type I error will help determine sample size.
c. Finding a significant difference in study groups occurs most often with smaller samples.
d. Sample size is especially important to support significant findings.

Question 2

Which of the following sets of terms represents an appropriate pairing of a probability sampling method and a corresponding nonprobability sampling one?

a. Cluster samplingsnowball technique
b. Simple random samplingconvenience sampling
c. Stratified random samplingquota sampling
d. Theoretical samplingquota sampling

CAPTAINAMERICA · **Reply #1 on:** Jul 8, 2018

Answer to Question 1

ANS: A
Evaluating the adequacy of the sample size is very important when no differences have been found. Too small a sample can result in no difference being detected, even when there actually is one.
Evaluating the possibility of a Type II error is a power analysis and will help determine sample size. Evaluating the adequacy of the sample size is very important when no differences have been found. Too small a sample can result in no difference being detected, even when there actually is one.
Too small a sample can result in no difference being detected, even when there actually is one.
Questions about the sample size occur when there are no significant findings. Evaluating the adequacy of the sample size is very important when no differences have been found. Too small a sample can result in no difference being detected, even when there actually is one.

Answer to Question 2

ANS: C
Stratified random sampling and quota sampling both attempt to balance the sample in terms of known characteristics in the population.
Cluster and snowball sampling methods do not have anything in common except that they create a sample for research.
Simple random and convenience sampling methods do not have anything in common except that they create a sample for research.
Theoretical and simple random sampling methods do not have anything in common except that they create a sample for research.