Lakhasly

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.

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.