NON – PROBABILITY SAMPLING (CONVENIENCE, PURPOSIVE).

Sampling is the act, process, or technique

of selecting a representative part of a

population for the purpose of determining

parameters or characteristics of the whole

population.

INTRODUCTION

Sampling is concerned with the selectionof a subset of individuals from populationto estimate characteristics of the wholepopulation.

Sampling is a process of collection ofdataSampling is a good representative of thepopulation.

MEANING OF SAMPLING

W. G. Cocharn: “In every branch of science we lack theresources, to study more than a fragment of thephenomena that might advance our knowledge”. In thisdefinition, a ‘fragment’ is the sample and ‘phenomena’ isthe ‘population’. The sample observation are applied tothe phenomena, i.e. generation.

David S. Fox: “In the social sciences, it is not possible tocollect data from every respondent relevant to our studybut only from some fractional part of that respondents.The process of selecting, the fractional, part is calledsampling. ‘Sampling design’ means the joint procedure ofselection and estimation. Sampling should be such thaterror of estimation is minimum.

DEFINITION OF SAMPLING:

The sampling method was used in social sciences research

as early as in 1754 by A.L Bowley.

When the population is very large, it can be satisfactorily

covered through sampling.

It saves a lot of time energy and money.

Especially when the units of an area are homogeneous,

sampling techniques is really useful.

When the data are unlimited, the use of this method is really

useful.

When cent percent accuracy is not required, the use of this

technique becomes inevitable.

When the number of individuals to be studied is

manageable intensive study becomes possible.

IMPORTANT OF SAMPLING

Characteristics of a Good Sample

•True representative•Free from bias•Objective•Accurate•Comprehensive •Economical•Approachable.•Good size•Feasible•Practical

ADVANTAGES OF SAMPLING

Reduced cost: It is economical.Greater Speed: Sampling is less time consuming than the census technique.Greater Scope: It has great scope and flexibility.Greater Accuracy: Sampling ensure high degree of accuracy due to a limitedarea of operation.

DISADVANTAGES OF SAMPLING

Less Accuracy: Conclusions derived from sampling are more liable to error.Changeability of units:Difficulties in selecting a truly representative sample: The results of asample are accurate and usable only when the sample is representative of the wholegroup.Need for specialized knowledge: Sampling method requires a specialisedknowledge in sampling technique statistical analysis and calculation of probableerror.

TECHNIQUES OF SAMPLING

•Probability sampling techniques.•Non – probability sampling techniques.

Probability sampling techniques: Probability samplingis a sampling technique wherein the samples are gatheredin a process that gives all the individuals in the populationequal chances of being selected.

According to G. C Halmstadter, “A probability sample isone that has been selected in such a way that every elementchosen has a known probability of being included.

TECHNIQUES OF PROBABILITY SAMPLING

Simple random sampling.Systematic sampling.Stratified samplingMultiple or double samplingMultistage SamplingCluster sampling.

NON – PROBABILITY SAMPLING

Non – probability sampling is a samplingtechnique where the samples are gathered ina process that does not all the individuals inthe population equal chances of beingselected.

In the absence of any idea of probabilitythe method of sampling is known as Non –probability sampling.

Characteristics of Non – Probability Sampling

There is no idea of population.There is no probability of selecting any individual.In has free distribution.The observations are not used for generalisation purpose.Non – parametric or non – inferential statistics are used.There is no risk for drawing conclusions.

Types of Non – Probability Sampling

oConvenience samplingoPurposive samplingoQuote samplingoIncidental samplingoSnowball sampling.

Convenience Sampling

This is also known as ‘accidental’ or“haphazard” samplingSample is selected according to the convenienceof the sample.No pre – planning is necessary for the selectionof items.The convenience may be in respect ofavailability of source list, accessibility of the units,etc.

EXAMPLES OF CONVENIENCE SAMPLING

The researcher engaged in the study of universitystudents might visit the university canteen, library,some departments, play ground, verandahs andinterview certain number of students.

Another example is of election study. Duringelection times, media personnel often present man– on – the – street interviews that are presumed toreflect public opinion. In this samplingrepresentativeness is not significant.

MERIT OF CONVENIENCE SAMPLING

Convenience sampling is quick and economical.Convenience sampling are best utilised forexploratory research when additional research withsubsequently be conducted with a probabilitysample.A convenience sampling may be used in any one ormore cases when the universes is not clearly defined.

DEMERIT OF CONVENIENCE SAMPLING

It is unscientific.It is a biased sampling method.Sampling unit is not clear.A complete source list is not available.

PURPOSIVE SAMPLING

•This sampling method is also known as judgementalsampling.•Appropriate characteristic required of the samplemembers.•Sampling is possible only when there is a specificobjective.•This method need not be used when there are multi– purpose objectives involved in the study.•The investigator has to pick up only such samplewhich is relevant to his study.• The investigator should possess full knowledge ofthe universe.

EXAMPLES OF PURPOSIVE SAMPLING

Suppose, the researcher wants to study beggars.He knows the three areas in the city where thebeggars are found in abundance. He will visit onlythese three areas and interview beggars of hischoice and convenience.

Popular journals conduct surveys in selectedmetropolitan cities to assess the popularity ofpoliticians and political parties or to forecastelection results.

MERITS OF PURPOSIVE SAMPLING

It uses the best available knowledgeconcerning the sample subjects.It give better control of significantvariables.In it sample group data can be easilymatched.In it there is homogeneity of subject usedin the sample.

DEMERITS OF PURPOSIVE SAMPLING

In it the reliability of the criterion is questionable.In it the knowledge of population is essential.In is there may be errors in classifying samplingsubjects.It is unable to utilise the inferential parametricstatistics.It is unable to make generalization convening totalpopulation.

CONCLUSION

On the basis of sample study, we can predictand generalise the behaviour of thepopulation.

Most researchers come to a conclusion oftheir study by studying a small sample from thehuge population or universe.