Question 1

Snowball sampling and judgment sampling are both non-probability sampling techniques.

Accepted Answer

Snowball sampling and judgment sampling are both non-probability sampling techniques, which means that the probability of any particular individual in the population being selected is not known. In snowball sampling, participants are selected based on referrals from others in the population, while in judgment sampling, the researcher selects participants based on their own judgment or expertise.

Question 2

Probability sampling is seen as less representative for the population than non-probability sampling.

Accepted Answer

Non-probability sampling is seen as less representative for the population than probability sampling, as it does not give all members of the population an equal chance of being selected for the sample.

Question 3

Which of the following sampling designs is a form of non-probability sampling?
A)Systematic sampling.
B)Area sampling.
C)Quota sampling.
D)Cluster sampling.

Accepted Answer

Quota sampling is a form of non-probability sampling where the researcher selects participants based on a pre-determined quota for certain characteristics (such as gender, age, ethnicity) instead of randomly selecting participants from the population. Systematic sampling, area sampling, and cluster sampling are all forms of probability sampling where each member of the population has a known and equal chance of being selected.

Question 4

The bigger the sample size,the better.

Accepted Answer

The answer of The bigger the sample size,the better....

Question 5

Convenience sampling and quota sampling are examples of probability sampling.

Accepted Answer

Convenience sampling and quota sampling are actually examples of non-probability sampling, as they do not involve random selection of participants from the population. Probability sampling methods, on the other hand, include simple random sampling, stratified random sampling, and cluster sampling.

Question 6

In probability sampling all elements of a population have a known and equal change to be included in the sample.

Accepted Answer

In probability sampling, each element in the population must have a known chance or probability of being selected for the sample. This ensures that the sample is representative of the population and helps to minimize bias.

Question 7

Simple random sampling is a method associated with a high degree of generalizability.

Accepted Answer

Simple random sampling involves randomly selecting participants from a population, which helps to ensure that the sample is representative of the population. This increases the generalizability of the sample and enhances the ability to make inferences about the entire population based on the sample results.

Question 8

What is the least reliable and least efficient probability sampling technique?
A)Systematic sampling.
B)Proportionate stratified sampling.
C)Disproportionate stratified sampling.
D)Cluster sampling.

Accepted Answer

Cluster sampling is the least reliable and least efficient probability sampling technique because it can introduce more sampling error and requires larger sample sizes compared to other techniques. It may also lead to less precision and accuracy in estimation. Therefore, it is not recommended as the best choice in many situations.

Question 9

If your objective is to compose a representative sample,what kind of sampling technique would you choose?
A)Simple random sampling.
B)Judgment sampling.
C)Convenience sampling.
D)Quota sampling .

Accepted Answer

Simple random sampling is the best choice for composing a representative sample because it ensures that each member of the population has an equal chance of being selected. This method eliminates the possibility of bias, making it an effective technique for creating a representative sample.

Question 10

When representativity is an important criterion for a study,which sampling technique would you choose?
a.Systematic sampling.
b.Judgment sampling.
c.Quota sampling.
d.Convenience sampling.

Accepted Answer

Systematic sampling ensures representativity by selecting every nth member of the population with a randomly chosen starting point, thus reducing bias and increasing the likelihood of a representative sample.

Question 11

If a sample is subdivided into subsamples,a minimal sample size of 30 is necessary for every subsample.

Accepted Answer

A sample size of 30 is the commonly accepted minimum sample size for statistical analysis, regardless of whether the sample is being subdivided or not. Therefore, this statement is true.

Question 12

Non-probability sampling leads to findings that are highly generalizable.

Accepted Answer

Non-probability sampling methods, such as convenience or purposive sampling, do not use random selection and therefore may not accurately represent the larger population. The findings may not be generalizable and may only reflect the characteristics of the sample that was selected.

Question 13

From statistical considerations the preference is given to probability sampling over non-probability sampling.

Accepted Answer

Probability sampling ensures that every member of the population has an equal chance of being selected for the sample, which makes the sample more representative of the population and minimizes the risk of bias. Non-probability sampling methods do not have this property and may result in a biased or unrepresentative sample. Therefore, statistically speaking, probability sampling is preferred over non-probability sampling.

Question 14

Cluster sampling is the least representative probability sampling design.

Accepted Answer

Cluster sampling is a probability sampling method in which the population is divided into groups (clusters), and then a random sample of clusters is selected. The elements within each selected cluster are then included in the sample. Cluster sampling is less representative than other probability sampling methods, such as simple random sampling or stratified sampling, because the clusters may not be representative of the entire population.

Question 15

Based on the desired accuracy and reliability of the research results,we can determine a desired sample size by a formula.The desired sample size is adjusted (and we then speak of an adjusted n)when:
A)The sample size is greater than 1000 persons.
B)The sample size is greater than 50 percent of the population.
C)The sample size is greater than 1 percent of the population.
D)None of the above answers is correct.

Accepted Answer

When the sample size is greater than 50 percent of the population, adjustments are often made to account for the diminishing returns of adding more samples and the increased likelihood of reaching most of the population. This is known as the finite population correction, which is applied to avoid overstating the precision of the study results when a large proportion of the population is sampled.

Question 16

With systematic sampling one divides the population into subgroups and chooses the test subject randomly from a number of randomly chosen subgroups.

Accepted Answer

Systematic sampling involves selecting every kth individual from a population list, not dividing the population into subgroups and choosing randomly from them. That description fits more closely with stratified sampling or cluster sampling.

Question 17

If a sample is subdivided into subsamples,a minimal sample size of 10 is necessary for every subsample.

Accepted Answer

The minimal sample size necessary for every subsample depends on the statistical analysis planned, the expected variability within the population, and the desired confidence level and power of the study, rather than a fixed number like 10 for all cases.

Question 18

Snowball sampling and Quota sampling are both non-probability sampling techniques.

Accepted Answer

Both snowball sampling and quota sampling are non-probability sampling techniques where the researcher does not have access to a complete list of the population, and the sample is not randomly selected.

Question 19

As a rule,probability sampling leads to a representative sample.

Accepted Answer

Probability sampling is a method of sampling where every member of the population has an equal chance of being selected. This leads to a representative sample as the sample reflects the characteristics of the population from which it was drawn.

Question 20

Stratified sampling and cluster sampling are examples of probability sampling.

Accepted Answer

Stratified sampling and cluster sampling are both examples of probability sampling, which means that each member of the population has an equal chance of being selected for the sample.

Quiz 13: Sampling