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SAMPLE DESIGN

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SAMPLE DESIGN

A sample design is a definite plan for obtaining a sample from a given population.

It gives an idea about the size of the sample.

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DIFFERENT METHODS FOR SELECTING SAMPLES

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DIFFERENT METHODS FOR SELECTING SAMPLES(SAMPLE DESIGNS)

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  • Random sampling(Probability sampling)
  • Non random sampling(Non probability sampling)

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PROBABILITY SAMPLING(RANDOM SAMPLING)

Each person in the population has equal, independent, and known chances of being selected.

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Probability Sampling May Be Divided Into Two:

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  • Simple random sampling
  • complex random sampling

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Classification Of Complex Random Sampling

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  • stratified sampling
  • systematic sampling
  • cluster sampling

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SIMPLE RANDOM SAMPLING

A simple random sample is a sample selected from a population in such a way that every member of the population has an equal chance of being selected and the selection of any individual does not influence the selection of any other

Random samples may be selected

  • by Lottery method
  • from table of random numbers

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LOTTERY METHOD

under this method, all items of the universe are numbered or named on separate slips of paper of identical size and shape. This slips are then folded and mixed up in a container. A blind fold selection is then made of the number of slips required to constitute the desired size of the sample. While preparing slips it must be seen that slips are of identical size, shape, colour etc. Otherwise there is a possibility of selecting a particular slip.

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TABLE OF RANDOM NUMBERS

Several standard tables of random numbers are available

(1)Tippets random number taples

(2)Fisher and yates tables etc.

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Tippets random number tuples

(Fisher and yates tables)

Tippets table of random numbers contains series of random digits arranged in rows and columns .These tables are used for getting random numbers corresponding to which we select items from population.

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MERITS AND DEMERITS OF SIMPLE RANDOM SAMPLING

  • Merits
  • There is no possibility of personal bias
  • The simple random sample usually represents population particularly when the sample size is large

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  • Demerits
  • It is often difficult to have an up to date list of all items of the population to be sampled
  • If the size of the sample selected is small,the results may not be reliable

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STRATIFIED SAMPLING

In this method divide the population into different sub population known as strata, such that items in each stratum are homogeneous. From each stratum, items are selected by simple random sample method. Stratified sampling method reduces time and expense to a greater extent.

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KINDS OF STRATIFIED SAMPLING

  1. Proportional stratified sample
  2. Disproportionate stratified sampling
  3. Stratified weighted sampling

Kin

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PROPORTIONAL STRATIFIED SAMPLING

Where number of items taken from each stratum is on the basis of size of each stratum.