Question

Give one situation where each of the sampling methods is being applied.
1. Lottery Sampling:
2. Systematic Sampling:
3. Stratified Random Sampling
4. Cluster Sampling
5. Multi-stage sampling​

Answer 1

Answer.

1. Lottery sampling : The lottery method of creating a simple random sample is exactly what it sounds like. A researcher randomly picks numbers, with each number corresponding to a subject or item, in order to create the sample. To create a sample this way, the researcher must ensure that the numbers are well mixed before selecting the sample population.
2. systematic sampling : Systematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size.
3. stratified random sampling : Stratified random sampling is a method of sampling that involves dividing a population into smaller groups–called strata. The groups or strata are organized based on the shared characteristics or attributes of the members in the group. The process of classifying the population into groups is called stratification.
4. Cluster sampling: Cluster sampling divides the population into groups, then takes a random sample from each cluster. Both systematic sampling and cluster sampling are forms of random sampling, known as probability sampling, which stands in contrast to non-probability sampling.
5. Multi stage sampling : The researcher divides the population into groups at various stages for better data collection, management, and interpretation. These groups are called clusters. For example, a researcher wants to know the different eating habits in western Europe.

Answer 2

Answer:

Situation where each of the sampling methods is being applied are as follows:

1. Lottery Sampling: It is used in real life for randomly drawing a winner in any lottery.
2. Systematic Sampling: A survey in which individual after every 1000th person needs to  be approached, then in that case we use Systematic Sampling.
3. Stratified Random Sampling: While calcullating data for a large number of people, when it gets tough to evaluate data of masses then we statistically collect data of few people and establish a relation in result.
4. Cluster Sampling: Dividing population into cluster and then analyzing a survey.
5. Multi-stage sampling​: used to collect data from a large, geographically spread group of people in national surveys

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