Simple Random Sampling -Criteria to choose -selecting a random sample

The easy random sample method is the one that is used most often. Every item in the community has an equal chance of being in the sample. This is called a simple random sample. Another thing is that choosing one thing for the sample shouldn't affect choosing another thing in any way. If the population is homogeneous, which means that all of the things in it have the same qualities that the researcher is interested in, then simple random picking should be used. Some of the things that can make people homogeneous are their age, gender, income, political, religious, or social beliefs, where they live, and so on.

A random number table is the best way to pick a simple random sample. The following things should be true of a random picking method.

  • There must be an equal chance for every person in the community to be in the sample.
  • The choice of one member is not changed by the choices of the members who came before.

The random numbers are a set of digits that are made by a system that uses probability. The random numbers are made up of the following:

  • There is an equal chance of each number (0,1,2,3,4,5,6,7,8,or 9) showing up anywhere. That's one tenth.
  • It doesn't matter where any two digits appear; they can happen in any two places.
To select a random sample using simple random sampling method we should follow the steps given below:
  1. Determine the population size (N).
  2. Determine the sample size (n).
  3. Number each member of the population under investigation in serial order. Suppose there are 100 members number them from 00 to 99.
  4. Determine the starting point of selecting sample by randomly picking up a page from random number tables and dropping your finger on the page blindly.
  5. Choose the direction in which you want to read the numbers (from left to right, or right to left, or down or up).
  6. Select the first ‘n’ numbers whose X digits are between 0 and N. If N =100 then X would be 2, if N is a four digit number then X would be 3 and so on.
  7. Once a number is chosen, do not use it again.
  8. If you reach the end point of the table before obtaining ‘n’ numbers, pick another starting point and read in a different direction and then use the first X digit instead of the last X digits and continue until the desired sample is selected.


  1. The simple random sample requires less knowledge about the characteristics of the population.
  2. Since sample is selected at random giving each member of the population equal chance of being selected the sample can be called as unbiased sample. Bias due to human preferences and influences is eliminated.
  3. Assessment of the accuracy of the results is possible by sample error estimation.
  4. It is a simple and practical sampling method provided population size is not large.


  1. If the population size is large, a great deal of time must be spent listing and numbering the members of the population.
  2. A simple random sample will not adequately represent many population characteristics unless the sample is very large. That is, if the researcher is interested in choosing a sample on the basis of the distribution in the population of gender, age, social status, a simple random sample needs to be very large to ensure all these distributions are representative of the population. To obtain a representative sample across multiple population attributes we should use stratified random sampling.


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