Sample Size – Institutional Effectiveness and Assessment (2024)

Many times those conducting surveys are told that larger samples are always preferable to smaller ones. This is not always necessarily the case. An array of factors, including degree of variability in the population, the degree of accuracy desired, and the analysis the results will be subject to, should be considered when deciding upon a sample size.

Degree of accuracy desired:Related to the subject of Power Analysis (which is beyond the scope of this site), this method requires the researcher to consider the acceptable margin of error and the confidence interval for their study. The online resource from Raosoft and Raven Analytics uses this principle.

Degree of variability (hom*ogeneity/heterogeneity) in the population:As the degree of variability in the population increases, so too should the size of the sample increase. The ability of the researcher to take this into account is dependent upon knowledge of the population parameters.

Number of different variables (subgroups) to be examined:As the number of subgroups to be examined increases, so too should the size of the sample increase. For example, should a researcher wish to examine the differences between ethnicities for a given phenomenon, the sample must be large enough to allow for valid comparison between each ethnic group.

Sampling ratio (sample size to population size):Generally speaking, the smaller the population, the larger the sampling ratio needed. For populations under 1,000, a minimum ratio of 30 percent (300 individuals) is advisable to ensure representativeness of the sample. For larger populations, such as a population of 10,000, a comparatively small minimum ratio of 10 percent (1,000) of individuals is required to ensure representativeness of the sample.

Response rate and oversampling:Are all the individuals in your sample likely to complete your questionnaire? If not, oversampling (sampling more individuals than would otherwise be necessary) may be required. Here the goal is to ensure that a given minimum raw count of respondents is met. While this is straightforward for a project using Simple Random Sampling, this can become increasingly complex as the number of variables to be examined grows, since the researcher must ensure that each critical subgroup attains the required response rate.

Statistical analysis desired:Specific minimum sample sizes are required for some statistical procedures, particularly those involving the investigation of multiple variables.

Other Online Resources

Sample Size Calculator (Raosoft)

Further Reading

Nardi, P.M. (2003).Doing survey research: A guide to quantitative methods. Boston, MA: Allyn and Bacon.
Neuman, W. L. (2007).Basics of social research: Qualitative and quantitative approaches(2nd ed.). Boston, MA: Allyn and Bacon.
Suskie, L.A. (1996). Questionnaire survey research: What works (2nd ed.). Tallahassee, FL: Association for Institutional Research

Sample Size – Institutional Effectiveness and Assessment (2024)


How many survey responses is enough? ›

As a very rough rule of thumb, 200 responses will provide fairly good survey accuracy under most assumptions and parameters of a survey project. 100 responses are probably needed even for marginally acceptable accuracy.

How do you know if the sample size is adequate for the study? ›

A good sample size really depends on the context and goals of the research. In general, a good sample size is one that accurately represents the population and allows for reliable statistical analysis.

What is the appropriate sample size for program assessment? ›

A general rule of thumb is to assess 10 students or 10% of the students, whichever is greater. However, there may be circ*mstances when other sample sizes may be favorable.

What is an appropriate sample size for needs assessment? ›

A good maximum sample size is usually 10% as long as it does not exceed 1000. A good maximum sample size is usually around 10% of the population, as long as this does not exceed 1000. For example, in a population of 5000, 10% would be 500. In a population of 200,000, 10% would be 20,000.

What is a statistically acceptable response rate for a survey? ›

So, what is a good survey response rate? Factors that impact this include, how engaged your customers are with your brand, and whether you're delivering surveys in a way that's easy for them. Nevertheless, a good survey response rate ranges between 5% and 30%. An excellent response rate is 50% or higher.

What is the rule of thumb for sample size? ›

Rule of Thumb #1: A larger sample increases the statistical power of the evaluation. Rule of Thumb #2: If the effect size of a program is small, the evaluation needs a larger sample to achieve a given level of power. Rule of Thumb #3: An evaluation of a program with low take-up needs a larger sample.

What is the 10 times rule for sample size? ›

The 10-times rule method

Among the variations of this method, the most commonly seen is based on the rule that the sample size should be greater than 10 times the maximum number of inner or outer model links pointing at any latent variable in the model (Goodhue et al., 2012).

How can you tell if sample size was adequate in qualitative research? ›

Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be put, the particular research method and purposeful sampling strategy employed, and the research product intended.

What is the best effective sample size? ›

Effective Sample (ESS) should be as large as possible, altough for most applications, an effective sample size greater than 1,000 is sufficient for stable estimates (Bürkner, 2017).

What is effective sample size sampling? ›

The effective sample size (ESS) is an estimate of the sample size required to achieve the same level of precision if that sample was a simple random sample. Mathematically, it is defined as n/D, where n is the sample size and D is the design effect. It is used as a way of summarizing the amount of information in data.

What is the least acceptable sample size? ›

Many statisticians concur that a sample size of 100 is the minimum you need for meaningful results. If your population is smaller than that, you should aim to survey all of the members. The same source states that the maximum number of respondents should be 10% of your population, but it should not exceed 1000.

Why do you need an appropriate sample size? ›

An appropriate sample renders the research more efficient: Data generated are reliable, resource investment is as limited as possible, while conforming to ethical principles. The use of sample size calculation directly influences research findings.

What is the sample size for a needs assessment survey? ›

We've put together some quick and easy 'rules of engagement' to help you understand what your sample size needs to be. A good maximum sample size is usually around 10% of the population, if this does not exceed 1000. Even in a population of 200,000, sampling 1000 people will normally give an accurate result.

Why is sample size important in research? ›

The sample size is a crucial consideration in research because it directly impacts the reliability and extent to which you can generalize those findings to the larger population. A larger sample size can potentially enhance the precision of estimates, leading to a narrower margin of error.

Is a 20% survey response rate good? ›

A good good NPS response rate is one that is above around 20%, subject to having enough total responses. You can see from this data published by CustomerGauge, using their extensive CustomerGauge NPS Benchmarks Survey, that most organisations (~51%) have response rates of 20% or higher.

Is 30 respondents enough for a survey? ›

While 30 is a good starting point for sample size, it is important to note that the optimal sample size will vary depending on the specific statistical test being used, the desired level of confidence, and the amount of variability in the population.

Is 20 respondents enough for quantitative research? ›

If the research has a relational survey design, the sample size should not be less than 30. Causal-comparative and experimental studies require more than 50 samples. In survey research, 100 samples should be identified for each major sub-group in the population and between 20 to 50 samples for each minor sub-group.

Is 5 respondents enough for a survey? ›

It's often a good idea (for qualitative research methods like interviews and usability tests) to start with 5 participants and then scale up by a further 5 based on how complicated the subject matter is.

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