sunandaC

New member
Definition
A probability sampling technique in which each element in the population has a known and equal probability of selection is known as simple random sampling (SRS). Every element is selected independently of every other element and the sample is drawn by a random procedure from a sampling frame.
Explanation
In random sampling, each element in the population has a known and equal probability of selection. Furthermore, each possible sample of a given size (n) has a known and equal probability of being the sample actually selected. This implies that every other element is selected independently of every other element. The sample is drawn by a random procedure from a sampling frame. This method is equivalent to a lottery system in which names are placed in a container, the container is shaken, and the names of the winners are then drawn out in an unbiased manner.

To draw a simple random sample, the researcher first compiles a sampling frame in which each element is assigned a unique identification number. Then random numbers are generated to determine which element to include in the sample. The random numbers may be generated with a computer routine or a table.
Advantages
• It is easy to understand
• The sample result may be projected to the target population.
Disadvantages
• It is often difficult to construct a sampling frame that will permit a simple random sample to be drawn.
• SRS can result in samples that are very large or spread over large geographic areas, thus increasing the time and cost of data collection.
• SRS often results in lower precision with larger standard errors than other probability sampling techniques.
• SRS may or may not result in a representative sample. Although samples drawn will represent the population well on average, a given simple random sample may grossly misrepresent the target population. This more likely if the size of the sample is small.
 

bhautik.kawa

New member
Definition
A probability sampling technique in which each element in the population has a known and equal probability of selection is known as simple random sampling (SRS). Every element is selected independently of every other element and the sample is drawn by a random procedure from a sampling frame.
Explanation
In random sampling, each element in the population has a known and equal probability of selection. Furthermore, each possible sample of a given size (n) has a known and equal probability of being the sample actually selected. This implies that every other element is selected independently of every other element. The sample is drawn by a random procedure from a sampling frame. This method is equivalent to a lottery system in which names are placed in a container, the container is shaken, and the names of the winners are then drawn out in an unbiased manner.

To draw a simple random sample, the researcher first compiles a sampling frame in which each element is assigned a unique identification number. Then random numbers are generated to determine which element to include in the sample. The random numbers may be generated with a computer routine or a table.
Advantages
• It is easy to understand
• The sample result may be projected to the target population.
Disadvantages
• It is often difficult to construct a sampling frame that will permit a simple random sample to be drawn.
• SRS can result in samples that are very large or spread over large geographic areas, thus increasing the time and cost of data collection.
• SRS often results in lower precision with larger standard errors than other probability sampling techniques.
• SRS may or may not result in a representative sample. Although samples drawn will represent the population well on average, a given simple random sample may grossly misrepresent the target population. This more likely if the size of the sample is small.

Hey Buddy,

I am also uploading a document which will give more detailed explanation on the Study on Simple Random Sampling.
 

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  • Study on Simple Random Sampling.pdf
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