## Note on Sampling and non sampling error and Types of sampling.

• Note
• Things to remember

### Sampling and non-sampling errors.

The error involves the collection processing and analysis of data are classified as two types They are

1. Sampling errors.
2. Non-random sampling.

#### Sampling errors.

A small portion of the population is taken as a sample and then studied. So that the results from the sample may not exactly some results from the population and certain amount of errors. This error is called sampling error. Sampling error is due to the following reason.

1. Faulty selection of sample size.
2. Improper choice of statistical method and way of sampling.
3. Faulty selection of sampling design. (random sampling and non-random sampling).

Types of sampling.

There are several methods of population units to be included in the sample on the basis of probability. The techniques of selecting a sample are classified as non-probability sampling and probability sampling. But in non-probability sampling,The probability of population units to be included in the sample are not considered, they are not sampling in the statistical sense. Therefore, they cannot be used for statistical inferences.

Generally, these are classified as.

1. Non-random sampling/ Non-probability sampling.
2. Random sampling/Probability sampling.

Non-random sampling.

This technique consists of the following methods.

1. Purposive sampling.
2. Quota sampling.
3. Convenience sampling.
4. Self-selected sample.
5. Snowball sampling.

1. Purposive sampling.

In this method, the researcher deliberately or purposively selects certain units for study from the population. The choice of the selection is supreme and nothing is left to chance. The particular units of the universe for constituting a sample on the basis that the small mass that they so select out of a huge one will be typical or representative of the whole. For instance, if economic conditions of people living in a state are to be studied, a few town and village may be purposively selected for intensive study on the principle of the that they can be representative of the entire state. Thus, the judgement of the organisers of the study plays an important role in the sampling design.

The defect of the mode are.

1. Errors of sampling rest upon hypothesis which is seldom met in practice.
2. The controls are not effective and often a biased sample is selected.
3. The knowledge of the population must be available, which in most cases is not possible.

But some of the merits of this method are.

1. If proper care is taken in selecting the sample to keep out any bias, the sample may represent the population.
2. This method is very cheap.
3. It is more useful especially when some of the units are very important and must be included.

2. Quota sampling.

This is considered to be special is the form of stratified sampling . According to this method, the population is first divided into different strata. Then the number of units to be selected from each other stratum is decided. This number is known as the quota. The field workers are generally asked to select the quota from the stratum according to their conveniences.

An example of this method includes that opinion surveys are mostly conducted by this method.

3. Convenience sampling.

In this method, a sample is selected taking the convenience of the sample into considerable. The convenience may be in respect of an availability of source list, accessibility of the units.

Although the method is most unscientific yet a quite a large number of a sample are selected according to this method. The method is to be used when.

1. The population is not clearly defined.
2. Sampling units are not clear.
3. A complete source list is not available.

4. Self-selected sample.

Sometimes a sample is not actually selected but people themselves come for inclusions in the sample.

For example, An enquiry has to be made about the people’s linking about a particular TV program and announcement to this effect is made on TV radio . Newspaper In such enquiry the sample is not fixed. Those who care to the reply form a part of the sample. Such a sample is called self-selected sample.

5. Snowball sampling.

It is a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances.

It uses a small pool of initial information to nominate, through their social networks, other participants who meet the eligibility criteria and could potentially contribute to a specific study. The term ‘snowball sampling’ reflects an analogy to a snowball increasing in size as it rolls downhill.

Snowball sampling is a method used to obtain research and knowledge from extended associations, through previous acquaintances. Snowball sampling uses recommendations to find people with the specific range of skills that has been determined as being useful.

An individual or a group receive information from different places through a mutual intermediary. This is referred to metaphorically as snowball sampling because as more relationship are built through mutual association, more connections can be made through those new relationships and a plethora of information can be shared can be shared and collected, much like the snowball that rolls and increase in size as it collects more snow. Snowball sampling is a useful tool for building the network and increasing the number of participants. However, the success of this technique depends greatly on the initial contact and connections made, thus it is important to correlate with those that are popular and honourable to create more opportunities to grow, but also to create a credible and dependent reputation.

Merits.

1. It is used to locate hidden populations.
2. It can be used in locating people of a specific population.

Demerits.

1. It is Non-Random.\
2. Community bias.
3. Vague overall sampling size.
4. Wrong anchoring.

Reference.

Kerlinger, F.N. Foundation of Behavioural Research. New Delhi: Surjeet Publication, 2000.

Kothari, C.R. Research Methodology. India: Vishwa Prakashan, 1990.

Singh, M.L. and J.M Singh. Understanding Research Methodology. 1998.

Singh, Mrigendra Lal. Understanding Research Methodology. Nepal: National Book centre, 2013.

1. A small portion of the population is taken as a sample and then studied. So that the results from the sample may not exactly some results from the population and certain amount of errors. This error is called sampling error.
2. The techniques of selecting a sample are classified as non-probability sampling and probability sampling.
3. Thus, the judgement of the organisers of the study plays an important role in the sampling design.
4. Snowball sampling is a method used to obtain research and knowledge from extended associations, through previous acquaintances. Snowball sampling uses recommendations to find people with the specific range of skills that has been determined as being useful.
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