Sampling & sampling procedure.pdf - Magadh University

SAMPLING & SAMPLING PROCEDURE

Dr. Meenakshi Shukla

Assistant Professor

Department of Psychology

Magadh University

Bodh Gaya

• Essentially, sampling consists of obtaining information from

only a part of a large group or population so as to infer about the

whole population. The object of sampling is thus to secure a

sample which will represent the population and reproduce the

important characteristics of the population under study as closely

as possible.

• A sample can yield more accurate results because the sources of

errors connected with reliability and training of field workers,

clarity of instruction, mistakes in measurement and recording,

badly kept measuring instruments, misidentification of sampling

units, biases of the enumerators and mistakes in the processing

and analysis of the data can be controlled more effectively. The

smaller size of the sample makes the supervision more effective.

Moreover, it is important to note that the precision of the

estimates obtained from certain types of samples can be

estimated from the sample itself.

SAMPLING

Sampling terminology

• Population : The word population is defined as the aggregate of units from which a sample

is chosen. If a forest area is divided into a number of compartments and the compartments

are the units of sampling, these compartments will form the population of sampling units.

On the other hand, if the forest area is divided into, say, a thousand strips each 20 m wide,

then the thousand strips will form the population. Likewise if the forest area is divided into

plots of, say, one-half hectare each, the totality of such plots is called the population of

plots.

• Sampling units : Sampling units may be administrative units or natural units like

topographical sections and sub-compartments or it may be artificial units like strips of a

certain width, or plots of a definite shape and size.

The unit must be a well defined element or group of elements identifiable in

the forest area on which observations on the characteristics under study could

be made. The population is thus sub-divided into suitable units for the purpose

of sampling and these are called sampling units.

• Sampling frame : A list of sampling units will be called a ‘frame’. A

population of units is said to be finite if the number of units in it is finite.

• Sample : One or more sampling units selected from a population according

to some specified procedure will constitute a sample.

• Sampling intensity : Intensity of sampling is defined as the ratio of the

number of units in the sample to the number of units in the population.

Sampling procedure

▪ In order to answer the research questions, it is doubtful that researcher

should be able to collect data from all cases. Thus, there is a need to select a

sample.

▪ The entire set of cases from which researcher sample is drawn in called the

population. Since, researchers neither have time nor the resources to analysis

the entire population so they apply sampling technique to reduce the

number of cases.

▪ Figure 1 illustrates the stages that researchers are likely to go through when

conducting sampling.

A. Stage 1: Clearly Define Target Population The first stage in the sampling process is to clearly define target population.

Population is commonly related to the number of people living in a particular

country.

B. Stage 2: Select Sampling FrameA sampling frame is a list of the actual cases from which sample will be

drawn. The sampling frame must be representative of the population.

C. Stage 3: Choose Sampling TechniquePrior to examining the various types of sampling method, it is worth noting

what is meant by sampling, along with reasons why researchers are likely to

select a sample. Taking a subset from chosen sampling frame or entire

population is called sampling. Sampling can be used to make inference about

a population or to make generalization in relation to existing theory. In

essence, this depends on choice of sampling technique.

In general, sampling techniques can be divided into two types:

▪ Probability or random sampling▪ Non-probability or non-random sampling

D. Stage 4: Determine Sample SizeIn order to generalize from a random sample and avoid sampling errors or biases, a randomsample needs to be of adequate size. What is adequate depends on several issues whichoften confuse people doing surveys for the first time. This is because what is important hereis not the proportion of the research population that gets sampled, but the absolute size ofthe sample selected relative to the complexity of the population, the aims of the researcherand the kinds of statistical manipulation that will be used in data analysis. While the largerthe sample the lesser the likelihood that findings will be biased does hold, diminishingreturns can quickly set in when samples get over a specific size which need to be balancedagainst the researcher’s resources (Gill et al., 2010).

E. Stage 5: Collect DataOnce target population, sampling frame, sampling technique and sample size have beenestablished, the next step is to collect data.

F. Stage 6: Assess Response Rate

Response rate is the number of casesagreeing to take part in the study. Thesecases are taken from original sample. Inreality, most researchers never achieve a100 percent response rate. Reasons for thismight include refusal to respond,ineligibility to respond, inability to respond,or the respondent has been located butresearchers are unable to make contact. Insum, response rate is important becauseeach non response is liable to bias the finalsample. Clearly defining sample, employingthe right sampling technique andgenerating a large sample, in some respectscan help to reduce the likelihood of samplebias.

Thank you…