Match List I with List II List I (Sampling techniques used in research) List…
2020
Match List I with List II
List I (Sampling techniques used in research) | List II (Description) |
|---|---|
A. Simple random sampling | I. The units are identified in terms of various specific features identified before drawing a sample structure |
B. Systematic sampling | II. Each unit is given an equal independent chance of being picked up |
C. Dimensional sampling | III. The k-interval is obtained by N/n and the units are drawn using the same, where N is the population size and n is the desired sample size |
D. Snowball sampling | IV. First member unit is used to identify the second unit and so on |
Answer: B. A - II, B - III, C - I, D - IV — Concept A sampling technique is identified by the rule that decides which population units enter the sample. Probability designs fix the selection…
- A.
A - I, B - IV, C - II, D - III
- B.
A - II, B - III, C - I, D - IV
- C.
A - IV, B - II, C - III, D - I
- D.
A - III, B - I, C - IV, D - II
Show answer & explanation
Correct answer: B
Concept
A sampling technique is identified by the rule that decides which population units enter the sample. Probability designs fix the selection probabilities in advance — either by giving every unit the same selection probability, so that every possible sample of the desired size is equally likely, or by walking a fixed interval through an ordered list from a random start. Non-probability designs instead fix the sample's structure beforehand from chosen characteristics, or let units already in the sample lead the researcher to the next ones.
Application
Technique | Selection rule and matching description |
|---|---|
Simple random sampling | Selection is left purely to chance: every unit of the population carries the same selection probability and every possible sample of the desired size is equally likely, with no interval, no pre-identified feature grid and no referral chain restricting the draw — description II |
Systematic sampling | The interval k is obtained as N/n from the population size N and the desired sample size n; one unit is then chosen at random within the first interval and thereafter every kth unit of the ordered list is drawn — description III |
Dimensional sampling | Various specific features (dimensions) are identified first, and the sample structure is drawn so that the chosen combinations of those features are represented — description I |
Snowball sampling | The first member unit contacted is used to identify the second unit, that unit identifies the next, and the sample grows through such referrals — description IV |
Cross-check
Descriptions II and III are both probability designs, and systematic sampling with a random start gives every unit the same selection probability n/N as well; the two are separated at the level of the whole sample. Simple random sampling makes every possible sample of the desired size equally likely, whereas a fixed interval k = N/n admits only the k samples that the k possible random starts can produce, leaving every other combination impossible. That structural restriction is what identifies the interval rule as systematic sampling rather than as the equal-chance description II.
Descriptions I and IV are both non-probability designs, but identifying units by specific features settles the sample's categories before any respondent is approached, whereas using the first member to reach the second discovers units only as fieldwork proceeds.
The quantities N and n appear only in the interval description, which ties that description to the technique that walks an ordered list at a fixed step rather than to any referral-based or feature-based technique.
Hence the correct match is A - II, B - III, C - I, D - IV.