# List I List II (Sampling method) (Description) (A) Stratified sampling (I) The units/members are chosen to represent various areas of characteristics

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 List I List II (Sampling method) (Description) (A) Stratified sampling (I) The units/members are chosen to represent various areas of characteristics so defined (B) Cluster sampling (II) Every unit had an independent and equal chance of being picked up (C) Systematic sampling (III) The units are groups and are chosen intact (D) Dimensional sampling (IV) The members are selected using the interval obtained by N/n – the N = Aggregate, n = desired sub-aggregate
Choose the correct answer from the options given below:
1. (A) - (I), (B) - (II), (C) - (III), (D) - (IV)
2. (A) - (III), (B) - (IV), (C) - (I), (D) - (II)
3. (A) - (IV), (B) - (I), (C) - (II), (D) - (III)
4. (A) - (II), (B) - (III), (C) - (IV), (D) - (I)

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Correct Answer - Option 4 : (A) - (II), (B) - (III), (C) - (IV), (D) - (I)

The correct solution is "A-(II), B-(III), C-(IV), D-(I)"

Sampling: is a process used in statistical analysis in which a predetermined number of observations are taken from a larger population. The methodology used to sample from a larger population depends on the type of analysis being performed, but it may include simple random sampling or systematic sampling.

Population: Set of all elements of interest in a study
Sample: Subset of population
Types of sampling:
• Probability sampling: is a sampling technique in which the researcher chooses samples from a larger population using a method based on the theory of probability. Probability samples are selected in such a way as to be representative of the population.
• Non-probability sampling: is a sampling method in which not all the members of the population have an equal chance of participating in the study, unlike probability sampling.
In the above question the sampling given is probability sampling, except for dimensional sampling, let us brief each one of them:
• Stratified sampling: In this type of sampling the population is divided into relatively homogeneous groups called strata based on their characteristics (gender, race, educational background). Once divided, each group is randomly sampled using another sampling method. It is suitable when the population is heterogeneous.
• Cluster sampling: Elements in the population are divided into separate groups called clusters. Each cluster is representative of the population as a whole. Cluster sampling is a method of probability that is often used to study large populations, particularly those that are widely geographically dispersed.
• Systematic sampling: is a probability sampling method in which researchers select members of the population at a regular interval ( or k) determined in advance.
•   k= N/n, where k is a systematic sampling interval, N is the population size and n is the sample size. Elements are chosen at uniform intervals.
• Dimensional sampling: is an extension to quota sampling. The researcher takes into account several characteristics example gender, age, income, residence and education. The researcher must ensure that there is at least one person in the study representing each of the chosen characteristics. It is a non-probability sampling type. For example: Out of 20 people the researcher ensures they have interviewed 5 male people (certain gender), 5 (certain age group) and 5 who have income between 30000 to 40000.

Therefore, it is clear from the above explanation that the answer to the above question is "Option 4".