Sampling methods are used in statistics to select a representative subset of data from a larger population. These techniques are used to make inferences about the entire population based on the characteristics of the sample.
Simple Random
Sampling: In this method, each member of the population has an equal chance of
being selected for the sample. A random number generator or a table of random
numbers is used to select the sample.
Explain the techniques
used in sampling method
Stratified
Sampling: In this method, the population is divided into groups or strata based
on some characteristic (e.g. age, gender, income, education level), and then a
random sample is taken from each stratum in proportion to its size.
Systematic
Sampling: In this method, a sample is chosen by selecting every nth member of
the population. For example, if the population size is 1000 and a sample of 100
is required, every 10th member of the population is selected.
Cluster
Sampling: In this method, the population is divided into clusters, and a random
sample of clusters is selected. Then, all members of the selected clusters are
included in the sample.
Convenience
Sampling: In this method, the sample is selected based on convenience, such as
selecting the first people who are available or who are willing to participate.
This method is generally less representative of the population and is subject
to bias.
It is important
to choose the appropriate sampling method based on the research question,
population characteristics, and available resources to ensure the sample is
representative and unbiased.
Sampling is a
statistical technique used to select a representative subset of a larger
population. The goal of sampling is to obtain information about the entire
population by studying only a portion of it. Sampling can be done using
different techniques, including:
Simple Random
Sampling: This is the most basic sampling technique. It involves selecting
random samples from the population with equal probability of selection. In this
method, each member of the population has an equal chance of being selected.
Systematic
Sampling: This technique involves selecting every nth member of the population,
starting with a randomly selected member. For example, if every 10th person is
selected, then the first person would be randomly selected, and every 10th
person after that would be included in the sample.
Stratified
Sampling: In this method, the population is divided into subgroups or strata
based on some characteristic, such as age or gender. Samples are then selected
from each stratum in proportion to their size, ensuring that each stratum is
represented in the sample.
Cluster
Sampling: In this technique, the population is divided into clusters based on
geography or some other characteristic. Clusters are then randomly selected,
and all members of the selected clusters are included in the sample.
Convenience
Sampling: This is the least rigorous method of sampling, in which samples are
selected based on convenience, availability, or accessibility. This method is
often used in exploratory studies, but it can lead to biased results.
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Purposive
Sampling: This method involves selecting a sample based on specific criteria,
such as expertise or knowledge about the subject. This method is often used in
qualitative research.
Overall, the
choice of sampling technique depends on the nature of the research question,
the characteristics of the population being studied, and the available
resources.