UGC Net Computer Science Paper 1 December 12 , Page 6 Solved
51. Which of the following sampling methods is based on probability ?
(A) Convenience sampling
(B) Quota sampling
(C) Judgement sampling
(D) Stratified sampling
Answer D
Explanation :-
Convenience Sample
A convenience sample is one of the main types of non-probability sampling methods. A convenience sample is made up of people who are easy to reach.
Consider the following example. A Company interviews shoppers at a local mall. If the mall was chosen because it was a convenient site from which to solicit survey participants and/or because it was close to the Company 's home or business, this would be a convenience sample.
Quota Sampling
A sampling method of gathering representative data from a group. As opposed to random sampling, quota sampling requires that representative individuals are chosen out of a specific subgroup. For example, a researcher might ask for a sample of 100 females, or 100 individuals between the ages of 20-30.
Judgment Sample
Judgment sample is a type of nonrandom sample that is selected based on the opinion of an expert. Results obtained from a judgment sample are subject to some degree of bias, due to the frame and population not being identical. The frame is a list of all the units, items, people, etc., that define the population to be studied.
For example, when interviewing manufacturers in the pharmaceutical industry to determine their preferred brand of equipment, the schedules, availability and willingness of the possible subjects are taken into account. Rather than performing random sampling and selecting subjects who are unavailable, an expert employs judgment sampling and selects units whose availability and attitude are compatible with the study.
Stratified Sampling
Stratified sampling refers to a type of sampling method . With stratified sampling, the researcher divides the population into separate groups, called strata. Then, a probability sample (often a simple random sample ) is drawn from each group.
Stratified sampling has several advantages over simple random sampling. For example, using stratified sampling, it may be possible to reduce the sample size required to achieve a given precision. Or it may be possible to increase the precision with the same sample size.
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