Best examples of sampling techniques lab report examples for statistics students

Before worrying about definitions, it helps to see how sampling shows up in real lab-style work. Below are realistic examples of sampling techniques lab report examples you might see in an undergraduate statistics or research methods course. Each one includes:

• The research question
• The population
• The sampling technique
• A short sample paragraph you could model your own writing on

These are not meant to be copied verbatim, but to show structure, tone, and level of detail expected in a statistics lab report.

Example of simple random sampling in a campus survey

Scenario
Research question: What proportion of first-year students at a large public university report sleeping fewer than 7 hours per night?
Population: All first-year undergraduates enrolled in the Fall 2024 semester.

Sampling technique
Simple random sampling using the registrar’s full list of first-year students.

Sample methods paragraph

We obtained a roster of all 3,842 first-year undergraduates enrolled in Fall 2024 from the registrar’s office. Using a random number generator in R, we selected 250 student IDs without replacement. Selected students received an email invitation to complete an online sleep habits questionnaire. Data were collected over a two-week period. This simple random sampling design ensured that each first-year student had an equal probability of selection, supporting unbiased estimation of the population proportion reporting fewer than 7 hours of sleep per night.

Why this works as a lab report example
This is one of the best examples of how to write about simple random sampling in a short lab: it states the frame (registrar list), the selection tool (random number generator), the sample size, and the logic of equal probability.

If you’re building your own examples of sampling techniques lab report examples, this structure—population → frame → random selection method → justification—should appear every time you use simple random sampling.

Example of stratified sampling using health data

Scenario
Research question: Does average daily screen time differ by gender among U.S. adolescents ages 12–17?
Population: U.S. adolescents ages 12–17.

Sampling technique
Stratified random sampling by gender (male, female, nonbinary/other) using an online panel.

Sample methods paragraph

To ensure adequate representation across gender identities, we used stratified random sampling. We partnered with an online survey panel provider that maintains a database of U.S. residents with self-reported demographic information. From this panel, we defined three strata based on gender: male, female, and nonbinary/other. Within each stratum, we drew a simple random sample of participants, targeting 200 adolescents per stratum (total N = 600). Stratification by gender increased the precision of between-group comparisons and prevented underrepresentation of smaller gender categories.

Why instructors like this example
It shows a clear reason for stratification (representation and precision), specifies the strata, and reports target sample sizes. When you look for examples of sampling techniques lab report examples that use stratified sampling, this kind of explanation—"we stratified by X to improve Y"—is exactly what graders expect.

For a real-world reference on how national surveys use stratified designs, you can skim the methodology sections of the National Health and Nutrition Examination Survey (NHANES) at the CDC: https://www.cdc.gov/nchs/nhanes/index.htm

Example of cluster sampling in an education study

Scenario
Research question: What is the average math test score among 8th-grade students in a large urban school district?
Population: All 8th-grade students in the district.

Sampling technique
Two-stage cluster sampling: schools as clusters, then classrooms within schools.

Sample methods paragraph

Because the district includes more than 90 middle schools, we used a two-stage cluster sampling design to reduce travel and administrative burden. In the first stage, we randomly selected 15 schools from the district’s list of middle schools, with selection probability proportional to 8th-grade enrollment. In the second stage, we randomly selected two 8th-grade math classrooms within each chosen school. All students in the selected classrooms were invited to participate (cluster sampling). This design allowed us to approximate a district-wide estimate of average math performance while limiting data collection to a manageable number of sites.

What this teaches you
Cluster sampling is common when the population is geographically dispersed or logistically hard to reach. This is one of the most realistic examples of sampling techniques lab report examples in education, because school-based studies almost never use pure simple random sampling of individual students.

For a high-level view of how large assessments use clustered designs, see the National Assessment of Educational Progress (NAEP) sampling overview: https://nces.ed.gov/nationsreportcard/tdw/sample_design/

Example of systematic sampling in a hospital waiting room

Scenario
Research question: What proportion of adult patients visiting an urban emergency department report using an urgent care clinic as an alternative for non-emergency issues?
Population: Adult patients (18+) visiting the emergency department during a 4-week period.

Sampling technique
Systematic sampling with a fixed interval.

Sample methods paragraph

During a four-week data collection period, research staff were present in the emergency department from 8:00 a.m. to 8:00 p.m. daily. Using systematic sampling, we approached every 5th adult patient who completed triage and was medically stable, as indicated by nursing staff. The sampling interval of 5 was chosen based on an expected daily volume of approximately 240 adult patients and a target sample size of 200 over the study period. If a selected patient declined participation or was ineligible, the next eligible patient was approached to maintain the approximate sampling interval.

Why this is a strong example
It explains how the interval was chosen and how exceptions were handled. When building examples of sampling techniques lab report examples for systematic sampling, always include the interval, time frame, and what happens when someone refuses or is ineligible.

For real clinical research guidelines, you can browse the NIH’s resources on study design: https://www.niaid.nih.gov/research/clinical-research-tools

Example of convenience sampling in a psychology lab

Scenario
Research question: Is there an association between daily social media use and self-reported stress among college students?
Population: All undergraduate students at a mid-sized private university.

Sampling technique
Convenience sampling from psychology courses.

Sample methods paragraph

We recruited participants using convenience sampling from three introductory psychology courses during the Spring 2025 semester. Instructors announced the study in class and posted the survey link on the course learning management system. Students who chose to participate completed an anonymous online questionnaire and received course extra credit. Because participants were drawn only from psychology courses, the sample may not be representative of the broader undergraduate population, particularly students from non-social science majors.

What this teaches you
This is one of the most honest examples of sampling techniques lab report examples you can use for convenience samples: it clearly acknowledges limitations and potential bias. Instructors care less that you used convenience sampling and more that you recognize what it does to generalizability.

Example of multistage sampling using public health data

Scenario
Research question: What is the prevalence of current e-cigarette use among U.S. adults ages 18 and older?
Population: U.S. civilian, non-institutionalized adults.

Sampling technique
Multistage probability sampling using existing national survey data.

Sample methods paragraph

Rather than collecting primary data, we conducted a secondary analysis of the 2023 National Health Interview Survey (NHIS), a nationally representative survey of the U.S. civilian, non-institutionalized population. NHIS uses a multistage probability sampling design that includes selection of geographic areas, households within those areas, and individuals within households. We restricted the dataset to adults ages 18 and older with complete information on e-cigarette use and applied the provided sampling weights to obtain nationally representative prevalence estimates.

Why this belongs in your toolkit
Many of the best examples of sampling techniques lab report examples in upper-level courses use secondary data. You don’t need to design the sampling yourself; instead, your job is to explain the existing design and how you used weights. For more on NHIS methodology, see: https://www.cdc.gov/nchs/nhis/index.htm

Example of quota sampling in market research

Scenario
Research question: How do attitudes toward plant-based meat alternatives differ by age group among U.S. adults?
Population: U.S. adults ages 18 and older.

Sampling technique
Nonprobability quota sampling by age group using an online survey platform.

Sample methods paragraph

We used quota sampling to obtain a sample that approximated the U.S. adult age distribution. Through an online survey platform, we set age quotas for four groups (18–29, 30–44, 45–59, 60+), based on recent U.S. Census estimates. Recruitment continued until each age quota was met (target N = 150 per group, total N = 600). Although participants were not selected using probability methods, age quotas helped prevent overrepresentation of younger adults, a common issue in online panels.

What you can copy from this style
When you use nonprobability methods, spell out exactly how quotas or caps were used. In examples of sampling techniques lab report examples that involve quota sampling, tying quotas to an external benchmark like Census data is a smart detail that signals you understand bias and representation.

How to write your own sampling section using these examples

Now that you’ve seen several examples of sampling techniques lab report examples, you can reverse-engineer a template for your own work. In almost every strong methods section, you’ll see the same backbone:

• A clear definition of the population you care about
• A description of the sampling frame (the list or process you sampled from)
• The sampling technique (simple random, stratified, cluster, systematic, convenience, quota, or multistage)
• The sample size and how you arrived at it
• A short justification for the method and a note on limitations

You can adapt wording like:

“We used [sampling method] because [reason: feasibility, representation, precision]. Our population was [description], and our sampling frame consisted of [list, database, or process]. We selected [N] participants using [random number generator, interval rule, course recruitment, etc.]. This approach may limit generalizability because [source of bias].”

The best examples of sampling techniques lab report examples don’t hide limitations; they explain them calmly and clearly.

Common mistakes to avoid when copying examples

When students look at examples of sampling techniques lab report examples, they often copy the structure but also inherit the bad habits. Watch out for:

• Calling a convenience sample “random” just because you used a random number generator on a small, non-representative pool.
• Forgetting to say when and where you collected data.
• Ignoring nonresponse; if many selected participants declined, mention it.
• Mixing up stratified and cluster sampling; strata are categories you sample within, clusters are natural groupings you often sample as a whole.

Your lab report doesn’t need to sound like a federal survey, but it should be specific enough that another student could replicate your sampling process from your description alone.

FAQ: examples of sampling techniques in statistics lab reports

Q1. Can I say I used random sampling if I only surveyed my friends?
No. That’s a classic mislabel. Surveying friends is convenience sampling, even if you “randomly” picked which friends to text first. To match the tone of the better examples of sampling techniques lab report examples, be honest: describe it as convenience sampling and briefly note how that limits generalizability.

Q2. What is a good example of stratified sampling in a student project?
A strong example of stratified sampling is a campus survey where you intentionally sample students by class year—first-year, sophomore, junior, senior—with a set number from each group. You might recruit 75 students from each class year so your comparisons of stress or GPA by year are more precise and not dominated by one large group.

Q3. Do I always need probability sampling in a statistics lab?
Not necessarily. Many introductory labs use convenience samples because of time and access limits. In that case, your job is to label the method correctly and discuss bias. Instructors care that you understand the difference between probability and nonprobability sampling and can interpret results accordingly.

Q4. Where can I find more real examples of sampling techniques in published research?
Look at the methods sections of open-access articles or government reports. The CDC, NIH, and U.S. Department of Education often publish technical documentation for their surveys. These documents show how professionals describe complex sampling designs in clear, structured language.

Q5. How long should the sampling section be in a typical lab report?
For a short statistics lab, two to four focused paragraphs are usually enough. If you follow the patterns in the examples above—population, frame, method, sample size, and limitations—you’ll hit the level of detail most instructors expect without over-writing.