How do you select and sample research populations and cases?

When you conduct research, you need to define your population and cases, which are the units of analysis you want to study. Depending on your research question, design, and method, you may need to select and sample from your population and cases in different ways. In this article, you will learn how to do that using analytical skills.

1 Population and cases

A population is the entire set of units that share a common characteristic or belong to a defined group. For example, if you want to study the impact of social media on political opinions, your population could be all the registered voters in a country. A case is a single unit that represents the population or a subset of it. For example, a case could be an individual voter, a social media post, or a political party. You need to identify your population and cases clearly and justify why they are relevant and appropriate for your research.

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2 Sampling frame and criteria

A sampling frame is a list or a representation of all the cases in your population that are accessible and available for your research. For example, if you want to survey voters, your sampling frame could be a voter registry or a phone directory. A sampling criterion is a rule or a condition that determines which cases are included or excluded from your sampling frame. For example, you may want to exclude voters who are under 18, live abroad, or have not voted in the last election. You need to define your sampling frame and criteria based on your research objectives, ethical considerations, and practical limitations.

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3 Sampling methods

A sampling method is a technique or a procedure that you use to select a sample from your sampling frame. A sample is a subset of cases that you actually collect data from. There are two main types of sampling methods: probability and non-probability. Probability sampling methods use random selection and allow you to make statistical inferences about your population based on your sample. For example, you can use simple random sampling, stratified sampling, or cluster sampling. Non-probability sampling methods use non-random selection and do not allow you to make statistical inferences about your population based on your sample. For example, you can use convenience sampling, purposive sampling, or snowball sampling. You need to choose your sampling method based on your research design, method, and question.

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Sacha C.

Research Consultant, NeuroLeadership Institute | Uniting neuroscience and strategy for business growth.
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Choosing the right sampling method is crucial. It’s the bridge between your theoretical population and the tangible data you’ll analyze. Whether you opt for probability or non-probability methods, your choice must align with the research objectives to ensure representativeness and accuracy.

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4 Sampling size and error

A sampling size is the number of cases that you include in your sample. A sampling error is the difference between the characteristics of your sample and the characteristics of your population. For example, if your sample has more female voters than your population, you have a sampling error. A sampling size and a sampling error are inversely related: the larger your sampling size, the smaller your sampling error, and vice versa. You need to determine your sampling size and error based on your desired level of precision, confidence, and variability.

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5 Sampling quality and validity

A sampling quality is the degree to which your sample represents your population accurately and reliably. A sampling validity is the degree to which your sample allows you to answer your research question effectively and meaningfully. For example, if your sample has a low response rate, a high non-response bias, or a high sampling bias, you have a low sampling quality and validity. You need to assess and improve your sampling quality and validity by using appropriate sampling methods, criteria, and techniques, and by reporting and addressing any sampling issues or limitations.

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6 Sampling skills and tools

A sampling skills are the abilities and competencies that you need to select and sample research populations and cases effectively and efficiently. For example, you need to have analytical skills, such as critical thinking, problem-solving, and data analysis, to design and implement your sampling strategy, to evaluate and interpret your sampling results, and to communicate and justify your sampling decisions. A sampling tools are the resources and instruments that you need to select and sample research populations and cases conveniently and practically. For example, you can use software, such as Excel, SPSS, or R, to generate random numbers, to calculate sample sizes, or to analyze sampling errors.

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Sacha C.

Research Consultant, NeuroLeadership Institute | Uniting neuroscience and strategy for business growth.
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The true discriminator in quality research isn't found in the software used but in the nuanced judgment, intuition, and the ability to see patterns where others don't. It's these intangible assets, paired with analytical prowess, that elevate a study from standard to exemplary. The human element, combined with the right tools, forms the backbone of profound, impactful research.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Sacha C.

Research Consultant, NeuroLeadership Institute | Uniting neuroscience and strategy for business growth.
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Every research study, irrespective of its scale or subject, offers an opportunity for learning. Reflect on the process – what went as expected, and what was surprising? These insights, whether they relate directly to your study or the broader research process, are valuable for both current analysis and future endeavors.

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How do you select and sample research populations and cases?

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1 Population and cases

2 Sampling frame and criteria

3 Sampling methods

4 Sampling size and error

5 Sampling quality and validity

6 Sampling skills and tools

7 Here’s what else to consider

Analytical Skills

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How do you select and sample research populations and cases?

1

2

3

4

5

6

7

1 Population and cases

2 Sampling frame and criteria

3 Sampling methods

4 Sampling size and error

5 Sampling quality and validity

6 Sampling skills and tools

7 Here’s what else to consider

Analytical Skills

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