Tips and a step-by-step plan for drawing a good sample

What is a sample?

A sample is a collection of elements from a population that share common characteristics. The sample serves as a representation of the population and is used to make generalizations that apply to the entire population. Sampling is essential because surveying the entire population, especially when it is extensive, is often unfeasible or impossible. By taking a sample, you can gather data efficiently and draw conclusions that accurately reflect the entire population.

Why work with a sample?

A sample is taken for several reasons, including:

• Efficiency: It may be practically impossible or too costly to gather data from an entire population. Sampling enables you to make conclusions about the population by studying a smaller subset of it.
• Time saving: Collecting data from the entire population can be time-consuming. Sampling, on the other hand, enables faster data collection and analysis, thus improving the efficiency of the research process.
• Cost savings: Conducting research on the entire population can be expensive, especially when the population is large or hard to reach. Sampling can significantly lower costs as it requires fewer resources for data collection and analysis.
• Practical feasibility: Sometimes, collecting data from the entire population is not practical because of various limitations, such as time, funding, or restricted access to the population. In such cases, conducting a sample research can make the study more manageable and feasible within these constraints.
• Accuracy: If a sample is taken correctly, it can provide precise estimates of the population’s characteristics. Statistical methods can be used to evaluate the accuracy of the sample results and estimate the level of uncertainty.

The selection of a particular sampling method depends on various factors, such as the nature of your research, the resources at hand, the characteristics of the population, and the research question. It is crucial to adequately justify the selected method and address any limitations in your thesis.

What is the difference between a random sample and a select sample?

There are two main methods of sampling: random sampling and selective sampling. The difference between the two sampling methods lies in how the sample is chosen and whether all members of the population have an equal chance of being selected.

Random sampling methods:

• In random sampling methods, all members of the population being studied have an equal opportunity to be included in the sample.
• This necessitates that all members of the population are identifiable and accessible, allowing for random selection.

An example would be selecting a sample from a customer base of an online store, where each email address has an equal probability of being chosen.

Select sampling methods:

• With certain sampling methods, not all members of the population have an equal probability of being included in the sample.
• The likelihood of being selected depends on the researcher’s discretion.

This approach is commonly employed when information about all members of the population is not readily obtainable or accessible.

For instance, when selecting a sample of customers from a supermarket, the researcher determines which customers are included in the sample due to the unavailability of a comprehensive list of all customers.

In summary, random sampling methods involve a completely random selection process where every individual in the population has an equal opportunity to be chosen. On the other hand, selective sampling methods depend on the researcher’s choice, resulting in unequal chances of selection for all individuals in the population.

Methods of sampling

Random sampling methods:

• Simple random sampling: You have access to a list containing all individuals in the population. Calculate the required sample size using a formula or an online calculator. Then, randomly select individuals from the list, for example, by using a random number generator. This can be done by inviting respondents through a link to an online questionnaire.
• Systematic simple random sampling: All individuals are listed in a file, and you systematically select each individual from the list. This requires that the order of the individuals in the list is completely random. This method can also be applied on the street, for example, by approaching every tenth person.
• Stratified sampling: The population is divided into homogeneous subgroups (strata), and then a sample is drawn from each subgroup. This ensures that each group is adequately represented in the sample. It is useful when comparing different groups within the study.
• Cluster sampling: In this case, entire groups of people are included in the sample instead of individuals. This can be applied, for example, when conducting research among school classes. It is practical when individual selection is not feasible.
• Multi-stage sampling: In some cases, it is necessary to select a sample in multiple steps. For example, first, randomly select municipalities, then randomly select companies within those municipalities, and finally, randomly select individuals within those companies.

Select sampling methods:

• Convenience sampling (random sampling): This method involves selecting respondents who happen to be available at a particular place and time. For example, approaching people passing by on the street or distributing surveys to students in a lecture hall. Although this method is quick and easy, it can negatively impact the representativeness of the sample because not all members of the population have an equal chance of being selected.
• Intuitive sampling and experience-based sampling: In intuitive sampling, the researcher relies on their intuition when selecting participants, while experience-based sampling involves selecting individuals or groups based on previous experience or knowledge. These methods can be helpful when no other methods are available, but they are prone to bias and should be used cautiously.
• Quota Sampling: Similar to stratified sampling, quota sampling divides the population and sample into homogeneous groups. However, quota sampling differs in that groups are selectively filled up to a predetermined quota. This approach is often used in market research and polls.
• Purposive Sampling: This method involves selecting specific subgroups from the population based on certain relevant characteristics for the study. This could be to investigate typical or extreme cases, create variation, or form homogeneous groups.
• Snowball Sampling: This method is utilized with hard-to-reach populations. The researcher begins with a small group of participants and then asks them to recommend other suitable respondents. This causes the sample size to grow, resembling the growth of a snowball.

Also, substantiate the validity and reliability of your sample in your thesis.

When discussing the validity and reliability of the sample in a thesis, it is important to emphasize the following points:

• Representativeness: Explain how the sample was selected and why it represents the entire population. Describe any steps taken to minimize bias, such as random selection or stratification.
• Sample size: Justify the chosen sample size and explain why it is sufficient for reliable conclusions. Address any practical limitations or available resources that influenced the sample size decision.
• Validity: Discuss how the sample contributes to the study’s validity. This includes both external validity, or the generalizability of the results to the population, and internal validity, or the validity of the conclusions within the sample.
• Reliability: Evaluate the sample’s reliability by considering the consistency and stability of the results. Highlight any measures taken to ensure reliability, such as the use of standardized sampling procedures.

Step-by-step plan for drawing up a good sample

When drawing a good sample, it is important to proceed carefully in order to obtain representative results. Here are some tips:

• Define your population: Clearly define the population your research aims to study. Ensure that you have a clear understanding of whom or what you intend to investigate.
• Select an appropriate sampling method: Choose the sampling method that aligns with your research question, available resources, and the nature of the population. Ensure that the chosen method serves the intended purpose of your research.
• Determine the sample size: Calculate the required sample size to draw reliable conclusions. Take into consideration factors such as population size, expected effect, desired accuracy, and confidence level.
• Ensure representativeness: It is crucial to have a representative sample that accurately reflects the entire population. This means including all relevant characteristics of the population in your sample, allowing for generalizability of findings to the overall population.
• Utilize random selection: If using a random sampling method, guarantee that each unit in the population has an equal chance of being included in the sample. This minimizes bias risks and enhances result reliability.
• Consistently collect data: Collect data in a standardized and consistent manner to minimize bias. Employ standardized instruments and procedures to ensure data reliability.
• Carefully analyze your data: After data collection, carefully analyze and interpret the results accurately and transparently. Be honest about any limitations of your sampling method and the generalizability of your findings.

By following these steps and considering the tips in this article, you can prepare a solid sample that serves as the foundation for a high-quality and dependable study.

Do you need help with quantitative research?

By following our tips, you can create a good sample that will yield representative and reliable results for your research. If you have doubts about the quality of your research or need assistance with statistics or the use of SPSS, professional help from Jouw Scriptiecoach is available. Our experts have extensive experience and have already assisted numerous students in writing and enhancing their theses. With the expertise of Jouw Scriptiecoach, you can elevate your research to the next level and confidently submit your thesis.