Choose the most appropriate answer from the options given below:

Which of the following are the types of probability sample?
A. Simple Random sampling
B. Proportionate stratified sampling
C. Disproportionate stratified sampling
D. Saturation sampling

Correct option is A

Probability sampling refers to sampling methods in which every member of the population has a known, non-zero chance of being selected. The following are types of probability sampling:

Simple Random Sampling (A) is a basic probability sampling technique where each member of the population has an equal chance of being selected.

Proportionate Stratified Sampling (B) involves dividing the population into strata and then selecting samples from each stratum in proportion to its size in the population. This ensures that the sample reflects the population's structure.

Disproportionate Stratified Sampling (C) is similar to proportionate stratified sampling, but the sample is taken in unequal proportions from each stratum, usually to ensure that smaller strata are represented more effectively.

Therefore, the correct answer is Option (a) A, B and C only because Saturation sampling (D) is not a probability sampling method.

Information Booster

1. Probability Sampling
Simple Random Sampling: Every member has an equal chance of selection (e.g., drawing names from a hat).
Systematic Sampling: Selecting every k-th individual (e.g., every 10th person on a list).
Stratified Sampling: Dividing the population into subgroups (strata) and sampling from each (e.g., urban vs. rural).
Cluster Sampling: Randomly selecting entire groups (clusters) for sampling (e.g., schools or neighborhoods).
Multistage Sampling: Combining cluster and random sampling (e.g., districts → schools → students).
Advantages: Generalizable, unbiased.
Limitations: Requires a complete population list, can be costly.

2. Non-Probability Sampling
Convenience Sampling: Selecting easily accessible individuals (e.g., mall surveys).
Purposive Sampling: Choosing participants based on specific criteria (e.g., experts).
Snowball Sampling: Existing participants recruit others (e.g., hidden populations).
Quota Sampling: Ensuring representation of subgroups (e.g., 50% men, 50% women).
Self-Selection Sampling: Participants volunteer (e.g., online surveys).
Advantages: Quick, cost-effective.
Limitations: Biased, not generalizable.

Key Considerations
Sampling Frame: List of the population.
Sample Size: Must be large enough for reliability.
Bias: Minimize selection bias for accurate results.

When to Use
Probability Sampling: For generalizable, quantitative research.
Non-Probability Sampling: For exploratory or qualitative studies.