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SAMPLING

The process of selecting a number of individuals

for a study in such a way that the individuals

represent the larger group from which they were

selected

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PURPOSE OF SAMPLING

•To gather data about the population in order to make an conclusion that can be generalized to the population.

•In order to carry out primary research it is necessary to use sampling.

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Steps Of Sampling Process

Identify your target population

Determine Sampling Frame

Determine Sampling Procedure( Technique to be used )

Determine Sample Size

Execute Sampling Design

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Techniques Of Sampling

Probability Sampling Non-Probability Sampling

Simple Random Sampling

Systematic Sampling

Stratified Sampling

Cluster Sampling

Convenience Sampling

Judgment Sampling

Quota Sampling

Snowball Sampling

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Probability Sampling

Simple Random Sampling

Here There is an Equal Probability of any Element to Receive the Treatment among the Population.

Applicable when population is small, homogeneous & readily available

Thus, It is Also Called Chance Sampling Or Probability Sampling.

For Example Drawing lots( Lottery Method ) or Using random number tables( Tippet’s Method )

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Probability Sampling

Systematic Sampling

In Some Instances the most practical way of sampling is to select every 15th name on a list, every 10th house on one side of a street and so on.

An Element of Randomness is usually introduced into this kind of sampling by using random numbers to pick up the unit with which to start.

This procedure is useful when sampling frame is available in the form of a list

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Probability Sampling

Stratified Sampling

If the population from which a sample is to be drawn does not constitute a homogeneous group then it is useful.

In this technique, the population is stratified into a number of non-overlapping sub-populations or strata and sample items are selected from each stratum.

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Probability Sampling

Cluster Sampling

It is useful when it would be impossible or impractical to identify every person in the sample.

Population is divided into groups, geographic area

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Non-Probability Sampling

Convenience Sampling

The process of including whoever happens to be available at the time is called “accidental” or “haphazard” sampling.

For Example - If a Researcher wishes to secure data from, say, Gasoline Buyers, he may select a fixed number of petrol stations and may conduct interviews at these stations. This would be an example of convenience sample of gasoline buyers.

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Non-Probability Sampling

Judgment Sampling

The sample is selected based upon judgment. - an extension of convenience sampling.

The researcher chooses the sample based on who they think would be appropriate for the study.

For Example - A Judgment sample of college students might be taken to secure reactions to a new method of teaching

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Non-Probability Sampling

Quota Sampling

Quota sampling is the non-probability equivalent of stratified sampling.

• First identify the stratums and their proportions as they are represented in the population

• Then convenience or judgment sampling is used to select the required number of subjects from each stratum.

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Non-Probability Sampling

Snowball Sampling

It is when you don't know the best people to study because of the unfamiliarity of the topic or the complexity of events. So you ask participants during interviews to suggest other individuals to be sampled.

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Random error- the sample selected is not representative of the population due to chance.

The level of it is controlled by sample size.

A larger sample size leads to a smaller sampling error.

Sampling Error

Random Sampling Error

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Sampling Error

Systematic Error

The level of it is not controlled by sample size.

Non-sampling Error

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