Sampling

Sampling-

In statistics, quality assurance, and survey methodology, sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. Each observation measures one or more properties (such as weight, location, color) of observable bodies distinguished as independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly stratified sampling. Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population.

Advantages of sampling 

1. Very accurate.

2. Economical in nature.

3. Very reliable.

4. High suitability ratio towards the different surveys.

5. Takes less time.

6. In cases, when the universe is very large, then the sampling method is the only practical method for collecting the data.

Disadvantages of sampling

1. Inadequacy of the samples.

2. Chances for bias.

3. Problems of accuracy.

4. Difficulty of getting the representative sample.

5. Untrained manpower.

6. Absence of the informants.

7. Chances of committing the errors in sampling.

Before you can calculate a sample size, you need to determine a few things about the target population and the sample you need:

1. Population Size — How many total people fit your demographic? ...

2. Margin of Error (Confidence Interval) — No sample will be perfect, so you need to decide how much error to allow.

Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected.

Reliance On Available Subjects. Relying on available subjects, such as stopping people on a street corner as they pass by, is one method of sampling, although it is extremely risky and comes with many cautions. This method,...