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Types of Probability Sampling Techniques: 1.The sampling interval tells the researcher how to select elements from a sampling frame by skipping elements in the frame before selecting one for the sample.Systematic Sampling Elements are randomly selected using a sampling interval.One way of obtaining a random sample is to give each individual in a population a number, and then use a table of random numbers to decide which individuals to include A specific advantage is that it is the most straightforward method of probability sampling.A disadvantage of simple random sampling is that you may not select enough individuals with your characteristic of interest, especially if that characteristic is uncommon.?2.


Original text

Types of Probability Sampling Techniques:



  1. Simple Random
    This method is used when the whole population is accessible and the investigators
    have a list of all subjects in this target population. From this list, we draw a random
    sample using lottery method or using a computer generated random list. One way of
    obtaining a random sample is to give each individual in a population a number, and
    then use a table of random numbers to decide which individuals to include
    A specific advantage is that it is the most straightforward method of probability
    sampling.
    A disadvantage of simple random sampling is that you may not select enough
    individuals with your characteristic of interest, especially if that characteristic is
    uncommon. It may also be difficult to define a complete sampling frame and
    inconvenient to contact them, especially if different forms of contact are required
    (email, phone, post) and your sample units are scattered over a wide geographical
    area.
    ▪ Example
    You want to select a simple random sample of 100 nurses of hospital X. You
    assign a number to every nurse in the company database from 1 to 1000, and use a
    random number generator to select 100 numbers.

  2. Systematic Sampling
    Elements are randomly selected using a sampling interval. The sampling interval
    tells the researcher how to select elements from a sampling frame by skipping
    elements in the frame before selecting one for the sample. If you need a sample size
    n from a population of size x, you should select every x/nth individual for the sample.


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