Sampling techniques:
Previously we have discussed about definite integral examples and In today's session we are going to discuss about Sampling techniques which comes under cbse books for class 11, Sampling is required when information is being processed for the transmission from one place to another place. The information is divided into samples and then the information is transmitted. It’s easy to remove noise or other factors from the samples in spite of the whole information directly.
If there are a lot items in a population set then the analysis process would be too costly and time consuming for that population. Like if the customer base id too large then it would be too costly to determine the satisfaction level of each customer. The sampling process defines the same thing in short.
Sampling is the risk that it's not representative of the population from which it is made . Basically sampling is the main step in analyzing any analytical process after that its not actually possible to remove errors.
The main processes for the sampling techniques are
· Determine objectives and population then
· Determining the sample size that would be created
· Selection of the sampling method
· Then the last step is to analyze the sampling errors regarding the projection or other
Sample size can be defined as
Sample size = reliability factor/Precision
There are several advantages of the sampling
· The actual air sample can be collected without any breakthrough
· No degradation problem of trapping material
· Moisture has no effect on sampling
· Duplicate analysis of the sample can be performed.
In mathematics it can be defined as to take a function f and recreate it with the help of only certain values.
Sampling techniques can be understood in probability or non probability preference. In probability method each member of the population has a non zero probability of being selected. This includes random, stratified and systemic sampling. In non probability method members are selected from the population in a random manner. It includes convent sampling, quota sampling, snowball sampling etc., techniques of sampling or methods for sampling are described below.
In Simple random sampling each member has an equal chance for being selected. It’s the purest method of sampling.
In systemic sampling every nth record is selected from the population.
Stratified sampling reduces the number of errors and used when one or more stratums have a low incidence relative to other.
Convenience sampling is used when inexpensive approximation of truth is required.
Judgment sampling is an extension of convenience sampling as the name indicates samples are made on the judgment basis.
Snowball sampling is used when desired sample characteristic is rare. It’s a difficult method and cost prohibitive too.
In the next session we are going to discuss Simple random sampling and You can visit our website for getting math help for free.
Previously we have discussed about definite integral examples and In today's session we are going to discuss about Sampling techniques which comes under cbse books for class 11, Sampling is required when information is being processed for the transmission from one place to another place. The information is divided into samples and then the information is transmitted. It’s easy to remove noise or other factors from the samples in spite of the whole information directly.
If there are a lot items in a population set then the analysis process would be too costly and time consuming for that population. Like if the customer base id too large then it would be too costly to determine the satisfaction level of each customer. The sampling process defines the same thing in short.
Sampling is the risk that it's not representative of the population from which it is made . Basically sampling is the main step in analyzing any analytical process after that its not actually possible to remove errors.
The main processes for the sampling techniques are
· Determine objectives and population then
· Determining the sample size that would be created
· Selection of the sampling method
· Then the last step is to analyze the sampling errors regarding the projection or other
Sample size can be defined as
Sample size = reliability factor/Precision
There are several advantages of the sampling
· The actual air sample can be collected without any breakthrough
· No degradation problem of trapping material
· Moisture has no effect on sampling
· Duplicate analysis of the sample can be performed.
In mathematics it can be defined as to take a function f and recreate it with the help of only certain values.
Sampling techniques can be understood in probability or non probability preference. In probability method each member of the population has a non zero probability of being selected. This includes random, stratified and systemic sampling. In non probability method members are selected from the population in a random manner. It includes convent sampling, quota sampling, snowball sampling etc., techniques of sampling or methods for sampling are described below.
In Simple random sampling each member has an equal chance for being selected. It’s the purest method of sampling.
In systemic sampling every nth record is selected from the population.
Stratified sampling reduces the number of errors and used when one or more stratums have a low incidence relative to other.
Convenience sampling is used when inexpensive approximation of truth is required.
Judgment sampling is an extension of convenience sampling as the name indicates samples are made on the judgment basis.
Snowball sampling is used when desired sample characteristic is rare. It’s a difficult method and cost prohibitive too.
In the next session we are going to discuss Simple random sampling and You can visit our website for getting math help for free.
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