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Sampling design


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  • 1.  A sample design is a definite plan for obtaining a sample from a given population . It refers to the technique or the procedure the researcher would adopt in selecting items for the sample . Sample design may as well lay down the number of items to be included in the sample, i.e. , the size of sample.
  • 2.  TYPE OF UNIVERSE – The universe can be finite or infinite. In finite universe the number of items are finite.  SAMPLE UNIT- A decision has to be taken concerning a sample unit before selecting sample. Sampling unit may be a geographical one such as state, district, village etc.
  • 3. * SOURCE LIST- It is also known as sample frame from which it is to be drawn . It contain the number of items of a universe. * SIZE OF SAMPLE- The size of sample should neither be excessively large, nor to small. It should be optimum.
  • 4. *PARAMETER OF INTEREST – In determining the sample design , one must consider the question of the specific population parameter which are of interest . * SAMPLING PROCEDURE – The researcher must be decide the type of sample he will use, i.e. , must decide about the technique to be used in selective items for sample.
  • 5.  PROBABILITY SAMPLING  NON PROBABILITY SAMPLING * PROBABILITY SAMPLING- 1 – Each and every unit of the population as the equal chance for selection as a sample unit. 2 – Also called formal sampling or random sampling . 3 – Probability sample allow us to estimate the accuracy of the sample.
  • 6.  SAMPLE RANDON SAMPLING – There are 2 type simple random sample : - 1 – WITH REPLACEMENT – Simple random sample the unit once selected has the chance for again selection. 2 – WITH OUT REPLACEMENT – Simple random sample the unit one selected can not be selected again.
  • 7.  SYSTEMATIC RANDOM SAMPLE - 1 – Order or unit in the sample frame based on some variables and then every Nnth number on the list is selected. 2 – Gaps between elements are equal and constant. 3 – N = SAMPLING INTERVAL
  • 8.  STRATIFIED RANDOM SAMPLING – Population is divided into 2 or more groups called strata according to some criteria such as - geographical location , great level , age and income and sub samples are randomly selected from each strata . Elements with in each strata are homogeneous but are heterogeneous across strata.
  • 9.  CLUSTER SAMPLING – The population is divided into sub groups like families a simple random sample is taken to the sub groups and then all members of the cluster selected are survey.
  • 10.  NON PROBABILITY SAMPLING – The probability of each case being selected from the total population is not known units of the sample are chosen on the basis of personal judgment or convenience there are no statical technique for measuring random sampling error in a non probability sample .  There are many point which are following as :-
  • 11.  1 – Involve non random method in selection of sample .  2 – All have not equal chance of being selected .  3 – selection depend upon situation .  4 – considerably less expensive .
  • 12.  QUOTA SAMPLING – 1 – The population is divided into cells on the basis of relevant control characteristics . 2 – A quota of sample units is established for each cell . 3 – A convenience sample is drawn for each cell until the quota is met . 4 – It is entirely non random and it is normally use for interview surveys .
  • 13. * JUDGEMENTAL SAMPLING – In judgmental sampling the judgment or opinion of same experts from the basis of sample method it is expected this samples would be suppose to know the population .
  • 14.  CONVENIENCE SAMPLING – In this , the researcher according to his convenience selects various sampling units . Often those elements are selected in the sample , which happen to be in right place and at right time . Example of convenience sampling include : -  1 – Use of students or members of some social organization research .  2 – Test out questionnaire in magazine and news paper .