Which factors are considered when determining the sample size for a qualitative study?

Which factors are considered when determining the sample size for a qualitative study?

When it comes to qualitative research, a number of factors need to be considered when organizing sample sizes. Below are four points to keep in mind when thinking about sample size:

Quality over quantity

Qualitative market research aims to tease out insights from a specific demographic, whether they are Midwest moms with household incomes above $60k, teens who play specific video games, or B2B decision makers. The main objective when conducting qualitative market research is ensuring the right people are recruited for the study. Depending on the study, pulling from a broad geographic region may be necessary for more accurate insights. As market researchers will tell you, there are wildly divergent opinions and experiences depending on where a person lives.

Researchers look for study respondents who meet all the criteria identified from quantitative research studies, in addition to the criteria set forth by the clients through their own research. Melding the populations from client lists and quantitative research will generate high-quality panels, rather than just recruiting from a general population. The quality of the output from well-curated panels is well worth the effort it takes to recruit them.

Choose the appropriate study design

The type of the qualitative study will determine the best sample size for your research. Will the study require in-depth interviews, ethnographic research, or focus groups? Some studies will blend all three, and perhaps more. Depending on which method or methods being used will determine the appropriate sample size. Each methodology for gathering feedback yields different outcomes. Experienced market researchers will quickly know which study design is best suited to the type of outcome their client is looking for. Equally important to the study design is the quality of questions being asked of the participants. An experienced and well-trained market researcher knows how to probe to get more nuanced answers from participants in a study group. Getting to the “how” and “why” is what makes qualitative market research so useful.

Pay attention to the Principle of Saturation

Sample sizes need to be large enough to adequately address the research questions being asked; however, too large a sample size brings the risk of repetitive data, also known as saturation. Market researchers know they have the appropriate sample size in a study when they’ve reached the saturation point. In other words, when answers or themes start becoming repetitive, the researcher can then shut down the study, knowing that saturation has been reached. There is diminishing return with larger samples, and more is not always better.

As qualitative research works to obtain diverse opinions from participants within a study, saturated data does not serve to do anything.

The objective of a qualitative study is to have a large enough sample size to expose a diversity of opinions while limiting the sample size at the point of saturation.

Does a magic number exist for qualitative research sample sizes?

After considering the above factors, there actually is a “magic” number for sample sizes. Based on research 30 seems to be an appropriate number for the most comprehensive assessment. Some studies are successful with as few as 10 participants, but this depends heavily on the quality of screening and recruiting the most appropriate participants.

If possible, in-depth interview studies should aim for sample sizes between 20-30, paying special attention to demographic and geographic profiles of your study recruits.

To learn more about recruiting the most appropriate participants for your next market research study, contact us here.

What is sample size?

Sample size is a frequently-used term in statistics and market research, and one that inevitably comes up whenever you’re surveying a large population of respondents. It relates to the way research is conducted on large populations.

So what is sampling, and why does sample size matter?

When you survey a large population of respondents, you’re interested in the entire group, but it’s not realistically possible to get answers or results from absolutely everyone. So you take a random sample of individuals which represents the population as a whole.

The size of the sample is very important for getting accurate, statistically significant results and running your study successfully.

  • If your sample is too small, you may include a disproportionate number of individuals which are outliers and anomalies. These skew the results and you don’t get a fair picture of the whole population.
  • If the sample is too big, the whole study becomes complex, expensive and time-consuming to run, and although the results are more accurate, the benefits don’t outweigh the costs.

If you’ve already worked out your variables you can get to the right sample size quickly with the online sample size calculator below:

Sample size calculator

Confidence Level:

Population Size:

Margin of Error:

Ideal Sample Size:

If you want to start from scratch in determining the right sample size for your market research, let us walk you through the steps.

Learn how to determine sample size

To choose the correct sample size, you need to consider a few different factors that affect your research, and gain a basic understanding of the statistics involved. You’ll then be able to use a sample size formula to bring everything together and sample confidently, knowing that there is a high probability that your survey is statistically accurate.

The steps that follow are suitable for finding a sample size for continuous data – i.e. data that is counted numerically. It doesn’t apply to categorical data – i.e. put into categories like green, blue, male, female etc.

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Stage 1: Consider your sample size variables

Before you can calculate a sample size, you need to determine a few things about the target population and the level of accuracy you need:

1. Population size

How many people are you talking about in total? To find this out, you need to be clear about who does and doesn’t fit into your group. For example, if you want to know about dog owners, you’ll include everyone who has at some point owned at least one dog. (You may include or exclude those who owned a dog in the past, depending on your research goals.) Don’t worry if you’re unable to calculate the exact number. It’s common to have an unknown number or an estimated range.

2. Margin of error (confidence interval)

Errors are inevitable – the question is how much error you’ll allow. The margin of error, AKA confidence interval, is expressed in terms of mean numbers. You can set how much difference you’ll allow between the mean number of your sample and the mean number of your population. If you’ve ever seen a political poll on the news, you’ve seen a confidence interval and how it’s expressed. It will look something like this: “68% of voters said yes to Proposition Z, with a margin of error of +/- 5%.”

3. Confidence level

This is a separate step to the similarly-named confidence interval in step 2. It deals with how confident you want to be that the actual mean falls within your margin of error. The most common confidence intervals are 90% confident, 95% confident, and 99% confident.

4. Standard deviation

This step asks you to estimate how much the responses you receive will vary from each other and from the mean number. A low standard deviation means that all the values will be clustered around the mean number, whereas a high standard deviation means they are spread out across a much wider range with very small and very large outlying figures. Since you haven’t yet run your survey, a safe choice is a standard deviation of .5 which will help make sure your sample size is large enough.

Now that you’ve got answers for steps 1 – 4, you’re ready to calculate the sample size you need. This can be done using the online sample size calculator above or with paper and pencil.

5. Find your Z-score

Next, you need to turn your confidence level into a Z-score. Here are the Z-scores for the most common confidence levels:

  • 90% – Z Score = 1.645
  • 95% – Z Score = 1.96
  • 99% – Z Score = 2.576

If you chose a different confidence level, use our Z-score table to find your score.

6. Use the sample size formula

Plug in your Z-score, standard of deviation, and confidence interval into the sample size calculator or use this sample size formula to work it out yourself:

Which factors are considered when determining the sample size for a qualitative study?

This equation is for an unknown population size or a very large population size. If your population is smaller and known, just use the sample size calculator above, or find it here.

What does that look like in practice?

Here’s a worked example, assuming you chose a 95% confidence level, .5 standard deviation, and a margin of error (confidence interval) of +/- 5%.

((1.96)2 x .5(.5)) / (.05)2

(3.8416 x .25) / .0025

.9604 / .0025

384.16

385 respondents are needed

Voila! You’ve just determined your sample size.

Troubleshooting your sample size results

If the sample size is too big to manage, you can adjust the results by either

  • decreasing your confidence level
  • increasing your margin of error

This will increase the chance for error in your sampling, but it can greatly decrease the number of responses you need.

What factors should be considered when determining the sample size for a qualitative study?

In general, three or four factors must be known or estimated to calculate sample size: (1) the effect size (usually the difference between 2 groups); (2) the population standard deviation (for continuous data); (3) the desired power of the experiment to detect the postulated effect; and (4) the significance level.

What are the consideration in determining the sample size?

When choosing a sample size, we must consider the following issues:.
What population parameters we want to estimate..
Cost of sampling (importance of information).
How much is already known..
Spread (variability) of the population..
Practicality: how hard is it to collect data..
How precise we want the final estimates to be..

What is the most important factor to consider when choosing to conduct a qualitative research?

Since qualitative studies are exploratory in nature it's important to avoid asking leading questions. Carefully examine, and better yet, have a second set of eyes examine your study to avoid leading questions, which can weaken your methodology. Data analysis.

What are the factors of qualitative research?

6 Critical Success Factors of a Qualitative Research Project.
Using the Right Methodology. ... .
Talking To the Right Person. ... .
Briefing Interviewers & Moderators. ... .
Note Taking or Transcripts. ... .
Reading Transcripts. ... .
Qualitative Analysis..