On Legal Research 05 - Sampling Methods

 

                                             

Sampling is the process of selecting a subset of a population to study the characteristics of the whole population. In the context of legal research, sampling can be used to study a variety of topics, such as the prevalence of crime, the effectiveness of different sentencing policies, or the attitudes of the public towards the law etc.

The sampling method is a technique used to select a subset of individuals or units from a larger population to conduct statistical analysis. It is an essential aspect of research design affecting the validity and reliability of the results.

Which type of sampling method to use entirely depends on the research goals and constraints. If the goal is to produce generalizable results, then probability sampling is the best choice. If the goal is to produce results quickly and cheaply, then non-probability sampling may be a better option.

    To choose an appropriate sampling method, the researcher should consider the following things:

i.      research objectives,

ii.     characteristics of the population,

iii.   availability of resources, and

iv.   ethical issues.


Types of Sampling Methods:

There are two primary types of sampling methods: probability sampling and non-probability sampling.

  • Probability Sampling:

Probability sampling is a type of sampling in which every member of the population has a known and equal chance of being selected. This type of sampling is the most statistically rigorous and is the most commonly used type of sampling in legal research. Probability sampling involves random selection, allowing the researcher to make strong statistical inferences about the whole population.

    The following are the kinds of probability sampling:

  a. Simple Random Sampling: Simple random sampling is a type of probability sampling in which each member of the population is assigned a number and then a random sample is selected from those numbers.

   b. Stratified Random Sampling: Stratified random sampling is a type of probability sampling in which the population is divided into groups (strata) and then a random sample is selected from each group (stratum).

  c. Cluster Random Sampling: Cluster random sampling is a type of probability sampling in which the population is divided into clusters and then a random sample of clusters is selected.

 d. Systematic Random Sampling: Systematic random sampling is a type of probability sampling in which a starting point is randomly selected from the population and then every Kth member of the population is selected after that.

 

Advantages and Disadvantages of Probability Sampling:

Probability sampling has the following advantages and disadvantages:

Advantages:

Representativeness: Probability sampling ensures that the sample is representative of the population, which means that the results of the sample can be generalized to the population.

Statistical rigor: Probability sampling allows researchers to calculate the margin of error and confidence level of their results, which makes the results more reliable.

Disadvantages:

Time and cost: Probability sampling can be time-consuming and expensive to conduct, especially if the population is large or dispersed.

Difficult to reach all members of the population: It can be difficult to reach all members of the population, especially if the population is marginalized or hidden.


  • Non-Probability Sampling:

Non-probability sampling is a type of sampling in which not every member of the population has a known and equal chance of being selected. This type of sampling is less statistically rigorous than probability sampling, but it can be more efficient and cost-effective. It involves non-random selection based on convenience or other criteria, allowing the collection of data easily. However, non-probability sampling may not represent the population and may introduce bias.

    The following are the kinds of non-probability sampling:

    a. Convenience Sampling: Convenience sampling is a type of non-probability sampling in which the researcher selects members of the population who are easy to access.

    b. Voluntary Response Sampling: Voluntary response sampling is a type of non-probability sampling in which the researcher selects members of the population who volunteer to participate in the study.

  c. Quota Sampling: Quota sampling is a type of non-probability sampling in which the researcher selects members of the population who meet certain criteria (e.g., age, gender, race/ethnicity) in certain proportions.

    d. Snowball Sampling: Snowball sampling is a type of non-probability sampling in which the researcher selects a small group of participants and then asks them to refer other potential participants to the study.


            Advantages and Disadvantages of Non-probability Sampling:

Non-probability sampling has the following advantages and disadvantages:

 Advantages:

 Efficient and cost-effective: Non-probability sampling is often more efficient and cost-effective to conduct than probability sampling.

Easy to reach participants: Non-probability sampling can be used to reach participants who are difficult to reach using probability sampling methods.

 Disadvantages:

 Representativeness: Non-probability sampling does not guarantee that the sample is representative of the population, which means that the results of the sample cannot be generalized to the population.

Sampling bias: Non-probability sampling is more prone to sampling bias than probability sampling. This means that the results of the sample may not be accurate or representative of the population.


        © YASIN AL RAZI

 

 

 

 

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