Sampling Technique is appropriate for the research title/topic
Provided 4 reasons to justify the choice of sampling technique
Answers
Answer:
Explanation:
Surveys would be meaningless and incomplete without accounting for the respondents that they’re aimed at. The best survey design practices keep the target population at the core of their thought process.
‘All the residents of the Dharavi slums in Mumbai’, ‘every NGO in Calcutta’ and ‘all students below the age of 16 in Manipur’ are examples of a population; they are countable, finite and well-defined.
When the population is small enough, researchers have the resources to reach out to all of them. This would be the best case scenario, making sure that everybody who matters to the survey is represented accurately. A survey that covers the entire target population is called a census.
However, most surveys cannot survey the entire population. This is when sampling techniques become crucial to your survey.
Why Is It Important?
Resource Constraints
If the target population is not small enough, or if the resources at your disposal don’t give you the bandwidth to cover the entire population, it is important to identify a subset of the population to work with – a carefully identified group that is representative of the population. This process is called survey sampling, and it is one of the most important aspects of survey design.
Whatever the sample size, there are fixed costs associated with any survey. Once the survey has begun, the marginal costs associated with gathering more information, from more people, are proportional to the size of the sample.
Drawing Inferences About the Population
Researchers are not interested in the sample itself, but in the understanding that they can potentially infer from the sample and then apply across the entire population.
A sample survey usually offers greater scope than a census. Working within a given resource constraint, sampling may make it possible to study the population of a larger geographical area or to find out more about the same population by examining an area in greater depth through a smaller sample.
Before we dive into the survey sampling methods at our disposal it is imperative that we develop a perspective on what an effective sample should look like.
3 Features to Keep in Mind While Constructing a Sample
Consistency
It is important that researchers understand the population on a case-by-case basis and test the sample for consistency before going ahead with the survey. This is especially critical for surveys that track changes across time and space where we need to be confident that any change we see in our data reflects real change – across consistent and comparable samples.
Diversity
Ensuring diversity of the sample is a tall order, as reaching some portions of the population and convincing them to participate in the survey could be difficult. But to be truly representative of the population, a sample must be as diverse as the population itself and sensitive to the local differences that are unavoidable as we move across the population.
Transparency
There are several constraints that dictate the size and structure of the population. It is imperative that researchers discuss these limitations and maintain transparency about the procedures followed while selecting the sample so that the results of the survey are seen with the right perspective.
Now that we understand the necessity of choosing the right sample and have a vision of what an effective sample for your survey should be like, let’s explore the various methods of constructing a sample and understand the relative pros and cons of each of these approaches.
Sampling methods can broadly be classified as probability and non-