ANUPAMBBA, LLB(Hons.)

2009-2014

Legal research, according to one source, is “the process of identifying and retrieving information necessary to support legal decision-making. In its broadest sense, legal research includes each step of a course of action that begins with an analysis of the facts of a problem and concludes with the application and communication of the results of the investigation.”

CENSUS METHOD

SAMPLING METHOD

Most research studies are based on samples. When a small group is selected as representative of the whole is known as sample method. The method of selecting for study, a portion of the universe with a view to draw conclusions about the universe in toto is known as 'sampling'.

Goode and Hatt defined sample as "a smaller representation of large whole". Nan Lin defines it as "a subject of cases from the population chosen to represent it". Thus, the whole group from which the sample has been drawn is known as 'universe or population' and the group selected for study is known as sample.

The sample should represent the characteristics of the population as closely as possible like a reflection in a mirror to the original.

Homogeneity amidst complexity

Possibility of representative selection

Absolute accuracy not essential

Saving of time Less expensive Detailed study Accuracy of result Administrative convenience Impossibility of the use of census

method Scientific base

Chances of bias Need of specialized knowledge Difficulties in sticking to sample Less accuracy Impossibility of sampling

Preparation of source list We must have a clear idea of the universe or the whole group from

which the sample is to be drawn. The universe should be a definite universe, i.e., the units can be definitely ascertained. The units of the definite universe should be listed out. This is called the source list

Deciding the sampling unit Before drawing a sample we have to decide the unit of sample. We

have to decide which type of the following sample units to be selected

Selecting the sampling techniques After deciding the sampling units to be selected from the source list.

The nature of population Number of classes proposed Nature of study Practical considerations Standard of accuracy Size of the schedule or questionnaire Nature of cases to be contacted Type of sampling method used

Probability Sampling Random Sampling Systematic Sampling Stratified Random Sampling Cluster Sampling Multi-stage Sampling

Non Probability Sampling Representative Sampling Judgment Sampling Accident Sampling Purposive Sampling

A sample which is not representative of the whole is called a biased sample. Representativeness may be absolute or universal, when the sample is similar to the universe in every respect. It may be relative or partial when the sample is similar to universe in certain aspects only. The representativeness actually means, the degree of similarity between the sample and universe. If the sample is not the representative of the whole, the results cannot be applied to the universe. If there is bias in sampling, there will be no use at all of the study

Too small size Purposive selection Imperfect stratification Incomplete source list Replacement or undue loss of cases Selection of cases by field workers Convenience 'sampling‘ Faulty method of drawing random

sample Nature of the phenomena

In a sample survey, a small portion of the population is studied. Though the sample is a representative of the whole, the results of the sample are bound to differ from the census results and there exists an error. This error is attributed to fluctuations of sampling and is called sampling error. The sampling error is present only in a sample survey and is completely absent in census method.

Sampling error may arise from chance and bias. There are unbiased sampling errors also. The unbiased errors are subject to the law of statistical regularity and tend to eliminate one another if the sample size is increased.

Faulty selection of the sample Substitution Faulty demarcation of sampling unit Error due to bias in the estimation

method Variability of the population