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Sampling Techniques and Procedures
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What Are Sampling Techniques?
Sampling techniques are effective sampling methods used by survey researchers to infer information or draw meaningful conclusions from a subset of the population without investigating every individual. These methods are fundamental in data science, data analysis, educational research, environmental monitoring, statistics, market research, product development, and survey research. Numerous researchers and analysts in various fields and industries use different types of sampling techniques to save time and money while gathering high-quality information for their quantitative research studies.
The sampling process requires using a small number of components or portions of the population to create conclusions. For instance, researchers generalize about a specific group of people or subjects based on a small sample of observations or a subset of a particular population. Additionally, this process allows researchers to estimate several unidentified characteristics or traits of a population of interest.
Types of Probability Sampling Techniques
Probability sampling techniques are cost-effective, simple, straightforward, and non-technical sampling techniques that use randomization to ensure that every component of the population has an equal chance to include in the selected sample. Also known as random sampling or representative sampling techniques, these methods select elements or traits such as test items, objects, and participants from a population. Researchers use probability sampling to make sure that the sample is representative of the population and to estimate the uncertainty level in the results, and to generalize the findings to the population.
Types of Non-Probability Sampling Techniques
Also referred to as non-random sampling, the non-probability sampling technique is a type of sampling method used by researchers and survey analysts when they select units from a population using a subjective method. However, there are some challenges when they use this sampling because it is difficult to estimate the probability of any one element taken in the sample. Still, researchers use non-probability sampling techniques due to the decline in response rates in probability surveys, the expensive cost of data collection, the need for access to real-time statistics, and the rise of non-probability data sources including social media and web surveys.
How to Conduct a Basic Sampling Technique
There are many ways to carry out probability and non-probability sampling techniques. If you want to conduct the basic sampling technique, follow the step-by-step procedure in this section.
Step 1: Specify the Population
Define the population with which you want to generalize your results for your survey research. Each study that you undertake has a different population of interest. Be clear and straightforward as the sample must be drawn from the population you want to generalize or the population you want to focus on.
Step 2: Create a List
Prepare a comprehensive list of the population from which to choose your sample. Be careful when compiling a list or using one that is already made. The list should be recent and exhaustive which means all the members must appear on the list. Having a ready-made list is better quality and cost-efficient than a newly made list.
Step 3: Draw the Sample
When you are done with the list of population members, use some rand sampling techniques such as using a table of random numbers and using computer programs. Don’t violate the random selection procedure and follow how to carry it out. Use the special functions of computer software like Excel to import the population lists into the database. Most database programs can generate a series of random numbers and a function for choosing a random sample from a range of entries found in the database.
Step 4: Contact Members of a Sample
Contact each of those chosen for the sample and collect the necessary information. However, if you are encountering challenges in your survey, use other sampling methods or research tools to reach them.
FAQs
The different types of sampling techniques are cluster sampling, simple random sampling, stratified sampling, and systematic sampling. Choose a sampling technique for your research study or experiment based on the major goals and objectives of your work. For example, if you prefer to investigate for sampling bias, use a random sampling technique. Some examples of random sampling techniques are cluster, stratified, and systematic sampling. There are two major sampling techniques used by researchers and analysts. These are probability sampling and non-probability sampling techniques. Use the sample error formula. Increase the sample size to yield a more accurate result and split the population into smaller groups. Apply random sampling and observe your target market for your survey campaigns.What are the different types of sampling techniques?
How to choose a sampling technique for research?
How many major sampling techniques are there in research?
How to reduce the sampling error?
It is integral to have a clear understanding of how you select participants for your survey research because it determines the population to which you may generalize your research findings. The accuracy and integrity of the overall survey research project are at risk if you perform poorly at the sampling stage of the research process. Thus, take note of the different types of probability and non-probability sampling techniques and how you conduct a simple random sampling technique. Sample.net provides other well-structured templates for survey reports and market research business plans.