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Random sampling is a process in which a set of individuals are selected from the entire population. It is selected in such a manner that all the individuals are selected randomly. In this process the individuals are chosen randomly that they are selected in any of the process during the sampling i.e they are adjusted in any of the sets of any individuals.
For example if you want to use random sampling on the computer for a specific population. The process includes-
Make a list of the elements used in the population on a spreadsheet.
A random number should be assigned to the elements defined in the population list.
The list should be sorted by the random numbers.
Take a print out of the list sorted by you.
The first n elements in the list consists of a random sample which means it is the output of the random elements in the given list of the population.
METHODS OF RANDOM SAMPLING
There are three methods of random sampling –
Random number tables – In this method tables are chosen randomly no matter whether they are chosen according to the size, row, column, vertical or diagonal.
Mathematical algorithms – It is a step – by – step calculation in processing the desired data.
Physical randomization devices–It includes the coins, playing cards and electronic random number indicating equipments for the sampling.
ADVANTAGES OF RANDOM SAMPLING
In random sampling every individual has a chance of being selected because selection is done randomly.
The results in random sampling are unbiased.
It is a method which tends the researcher to work with great speed.
It is economical and less expensive.
The validity of the results increase for the researchers as they can easily draw the desired conclusions and guesses from the given statisticsdata.
DISADVANTAGES OF RANDOM SAMPLING
To achieve high targets lots of money, labour and time is required.
Since the data is restricted so the individual frames are very difficult to obtain.
Less chance of accuracy exists in random sampling in comparison to the other methods of sampling.
PROBABILITY BASED RANDOM SAMPLING
In probability based random sampling the probability of the selection of each and every elements exist with a set of designed variables.
There are four methods of probability based random sampling
Simple random sampling – It collects the samples in such a form that the samples are not replaced in any of the ways.
Stratified random sampling – It has a tendency to control or restrict the sub – sample sizes defined by one or more variables.
Cluster based random sampling – It has a tendency to form the samples in groups or clusters so that the cost of the data collection increases at a specified time.
Multi stage random sampling – at different stages groups of elements are selected from the sampling frame.
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