Management Accounting · Summarising and analysing data

Sampling Methods: How to Choose the Right One in ACCA MA

Updated 11 October 2026 · Fact-checked

Sampling means studying a part of a population to learn about the whole. Random, systematic, stratified, cluster and multistage methods use chance selection. Quota sampling does not. To answer an exam question, spot the clue in the scenario (list available, groups, cost, geography) and match it to the method.

Understand Sampling Methods

A population is every item you want information about, such as all customers, invoices or employees. Checking all of them is a census. It is often too slow or costly, so you take a sample: a smaller group chosen to represent the population.

A sampling frame is the list from which you pick the sample. Methods split into two families. Probability (random) methods give every item a known chance of selection, so you can measure sampling error. Non-probability methods rely on judgement, so bias is harder to measure.

Simple random sampling: every item has an equal chance, picked using random numbers. It is unbiased but needs a full list and may miss small groups.

Systematic sampling: choose a random start, then take every nth item. It is quick and simple. It can give bias if the list has a pattern that matches n, for example every 7th day always being a Sunday.

Stratified sampling: split the population into groups (strata) that differ from each other, such as department. Then sample randomly from each stratum, usually in proportion to its size. It makes sure every group is represented and gives more precise results, but you need to know the strata in advance.

Cluster sampling: split the population into groups that each look like a small version of the whole, such as stores in different towns. Pick some clusters at random and study all items in them. It is cheap when the population is spread out, but it is less precise if clusters differ from each other.

Multistage sampling: sample in stages, for example choose regions, then towns in those regions, then households in those towns. It saves cost over large areas but errors can build up at each stage.

Quota sampling: the interviewer must find a set number of people from each category (for example 50 men and 50 women) but picks them by judgement. It is quick, cheap and needs no sampling frame. It is not random, so bias is likely and sampling error cannot be measured.

Key formulas to remember

Systematic sampling interval: Interval (n) = population size ÷ sample size; Pick a random start within the first n items, then take every nth item. Round sensibly if the answer is not whole.
Proportionate stratified sample: Sample from a stratum = (stratum size ÷ population size) × total sample size; Use this to allocate the sample across strata. Round so the total still equals the sample size.
Stratified vs cluster rule: Stratified: sample from every group. Cluster: sample all items from some groups.; Strata should differ from each other and be similar inside. Clusters should each resemble the whole population.

How to solve Sampling Methods questions

Use this method for any sampling question, whether it asks you to name a method, describe it or calculate a sample.

1Read the scenario and note the population, whether a full list exists, and any limits on cost, time or geography.
2Decide if the question needs a random method or a non-random one. Words like 'interviewer chooses', 'quota' or 'judgement' point to non-random.
3Look for group clues. If every group must be represented, think stratified. If groups are geographic and cheap access matters, think cluster or multistage.
4If the question gives a list and asks for a regular pattern, think systematic. If every item must have equal chance, think simple random.
5For a calculation, work out the interval or the proportion for each stratum, and check the total equals the required sample size.
6Match the answer to the wording. Names must be exact, and any advantage or disadvantage must fit the scenario.
7Check that your choice is consistent. Do not call a method random if the selector chooses by judgement.

Quickest way: Clue-word matching

When to use it: Use it for one-line multiple choice questions where you have under two minutes.

Underline the clue: 'every nth' means systematic, 'quota' means non-random, 'regions then towns' means multistage.
'Some groups, all items inside' means cluster. 'All groups, some items from each' means stratified.
If a calculation is needed, do interval = population ÷ sample, or stratum share × sample, and check the total.
Eliminate options that call quota sampling random or that say a method has no bias.

Common mistakes in Sampling Methods

Confusing stratified and cluster sampling.
Both split the population into groups.
Fix: Stratified takes some items from every group. Cluster takes every item from some groups.
Calling quota sampling a random method.
Quotas look like strata, which sounds structured.
Fix: In quota sampling the interviewer picks people by judgement. Stratified picks randomly within each group.
Saying systematic sampling always gives a biased sample.
Students over-remember the pattern warning.
Fix: Bias arises only if the list has a regular pattern matching the interval. Otherwise it behaves much like random sampling.
Rounding stratum sizes so the total is wrong.
Each figure is rounded on its own.
Fix: Add the rounded numbers and adjust the largest stratum if the total does not match the sample size.
Choosing simple random sampling when no sampling frame exists.
It is the first method taught.
Fix: Simple random needs a complete list. Without one, consider cluster, multistage or quota.

Worked examples

Example 1

A company has 2,000 invoices and wants a systematic sample of 80. The random start is invoice 7. Find the interval and the first three invoices selected.

Show the solution

Interval = 2,000 ÷ 80 = 25.
First invoice = 7.
Second = 7 + 25 = 32.
Third = 32 + 25 = 57.

Answer: Interval 25. Invoices 7, 32 and 57.

Example 2

A firm has 600 staff: 300 in production, 200 in sales and 100 in admin. It wants a proportionate stratified sample of 60 staff. How many from each department?

Show the solution

Production = 300 ÷ 600 × 60 = 30.
Sales = 200 ÷ 600 × 60 = 20.
Admin = 100 ÷ 600 × 60 = 10.
Check: 30 + 20 + 10 = 60.

Answer: 30 production, 20 sales, 10 admin.

Exam tips

Learn one-line definitions for all six methods. Many objective questions are pure recognition.
In multiple response questions, read how many answers to select, and check each statement against the method.
For 'which method is most suitable' questions, match to the scenario constraint such as cost, spread or need for representation.
Remember only probability methods allow sampling error to be measured. This is a frequent right-or-wrong statement.

Practice questions from Summarising and analysing data

Sampling Methods in other exams

The same ground in other exams, if you are preparing for more than one or want another angle on it.

ACCA Applied SkillsAudit Sampling and Selecting Items for Testing

Sampling Methods: frequently asked questions

What is the difference between stratified and cluster sampling?

In stratified sampling you divide the population into different groups and sample from every group. In cluster sampling you pick some groups at random and study everything inside them. Stratified aims for precision, cluster aims for lower cost.

Is quota sampling random?

No. The interviewer chooses who to ask until each quota is full. Because selection is by judgement, bias is likely and sampling error cannot be measured.

How do I choose a sampling method in the ACCA MA exam?

Look at the scenario clues: is a full list available, are there distinct groups, is the population spread out, and how tight are cost and time? Then match the clue to the method and its main advantage.

When is multistage sampling used?

It is used when the population is large and spread across an area. You sample in stages, such as regions, then towns, then households. It cuts travel and cost but can add error at each stage.