Randomisation in Psychology: Concept, Methods, and Examples
In psychological research, randomisation is a simple yet powerful technique used to reduce bias and improve the reliability of experimental results. Alongside counterbalancing and standardisation, it helps ensure that experiments are fair and that findings are valid.
This article explains what randomisation is, how it’s used in psychology, and the different methods researchers apply to achieve truly unbiased results.
What Is the Concept of Randomisation in Psychology?
Randomisation refers to the process of using chance to decide the order of conditions, the allocation of participants, or the presentation of materials in a psychological experiment.
Its main purpose is to control for extraneous variables — factors other than the independent variable that could influence results. By randomising elements of an experiment, researchers can be more confident that any changes in the dependent variable are due to the independent variable, not accidental bias.
Example:
If a psychologist is testing whether background music affects memory recall, randomisation might be used to:
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Randomly allocate participants to “music” or “no music” conditions.
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Randomly determine the order in which word lists are presented.
This ensures fairness and prevents one condition from consistently being easier or harder than another.
Randomising participants helps reduce bias — but it’s also important to control for investigator effects in psychology, where the behaviour of the researcher can affect outcomes regardless of allocation.
Randomisation improves internal validity, but psychologists also need to think about ecological validity — ensuring results can be generalised to real-life situations.
Why Is Randomisation Important in Psychology?
Psychological experiments aim to uncover cause-and-effect relationships. However, bias, order effects, and participant differences can threaten validity.
Randomisation helps to:
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Reduce investigator bias: Prevents the researcher’s expectations from influencing results.
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Balance participant variables: Ensures characteristics like motivation or ability are evenly distributed.
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Increase internal validity: Makes it more likely that changes in behaviour are due to the manipulation of the independent variable.
👉 For a breakdown of other key control techniques, see Experimental Designs in Psychology: Types, Examples, and Key Differences.
Randomisation strengthens both reliability and internal validity by preventing systematic bias.
What Are the 4 Methods of Randomisation?
There are several ways researchers can apply randomisation in psychological studies. The most common four are:
1. Simple Randomisation
Participants or stimuli are assigned purely by chance — often using a random number generator or drawing names from a hat.
Example: Each participant has an equal chance of being in the experimental or control group.
2. Block Randomisation
Used when experiments involve several conditions or trials. Participants are divided into “blocks,” and within each block, conditions are randomised.
Example: In a memory test with three conditions (quiet, soft music, loud music), each block of participants experiences these conditions in a random order.
3. Stratified Randomisation
Ensures key participant variables (e.g. age, gender, IQ) are balanced across conditions. Participants are grouped into “strata” based on these variables, and then randomised within each group.
Example: Equal numbers of males and females are randomly assigned to each condition.
4. Systematic Randomisation
Combines random selection with a consistent rule or pattern.
Example: A researcher randomly selects a starting participant, then includes every 3rd person on the list.
Example of Randomisation in Psychology
Let’s imagine a study investigating whether studying in the morning or evening improves concentration.
Without randomisation, if all “morning” participants happen to be early risers and “evening” participants are night owls, the results could be biased.
By randomly assigning participants to conditions, these personality differences are evenly distributed — producing more reliable data.
Randomisation vs Counterbalancing
Although both randomisation and counterbalancing aim to reduce bias, they serve different purposes:
| Technique | Purpose | Example |
|---|---|---|
| Randomisation | Controls participant or investigator bias by using chance | Randomly allocate participants to groups |
| Counterbalancing | Controls order effects in repeated measures designs | Half complete A→B, others B→A |
💡 Tip: These techniques are often used together. In a repeated measures design, researchers might randomly assign participants to different order sequences (a form of randomised counterbalancing).
For a clear explanation of how counterbalancing works in practice, read:
👉 What Is Counterbalancing in Psychology?
How Randomisation Improves Experimental Design
Randomisation is crucial for achieving control in psychological research — one of the three core features of a well-designed experiment (alongside manipulation and measurement).
When combined with appropriate design choices — such as independent or repeated measures designs — it ensures that findings are both valid and generalisable.
Along with counterbalancing, standardisation helps keep experiments consistent and free from bias.
Randomisation is one of several techniques used to control extraneous and confounding variables that can otherwise threaten the validity of research.
Randomisation also helps reduce the impact of demand characteristics by preventing participants from predicting the order or purpose of conditions.
Randomisation helps reduce bias, strengthening both validity and reliability in psychology by making results more repeatable.
Randomisation in A-Level Psychology (AQA)
In AQA Psychology, randomisation is taught within the Research Methods unit. Students are expected to:
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Define randomisation.
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Explain why it’s used to control extraneous variables.
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Apply it to experimental scenarios.
Exam-style tip:
“Randomisation prevents investigator effects and ensures all participants have an equal chance of experiencing each condition, improving internal validity.”
Frequently Asked Questions
1. What is the concept of randomisation?
Randomisation is the use of chance to decide how participants or conditions are arranged, reducing bias and improving validity.
2. What are examples of randomisation in psychology?
Examples include randomly assigning participants to groups or randomising the order of word lists in a memory test.
3. What are the 4 methods of randomisation?
Simple, block, stratified, and systematic randomisation.
4. How can randomisation be used in psychological research?
Researchers use randomisation to control variables that could unfairly influence results — such as order effects, researcher bias, or participant differences.
Conclusion
Randomisation is a core principle of good psychological research. By using chance to assign participants or conditions, psychologists reduce bias and improve the fairness and accuracy of their results.
Whether it’s deciding the order of trials or allocating participants, randomisation — along with counterbalancing and standardisation — ensures that experiments truly measure what they intend to measure.
To see how randomisation supports different types of validity, check out our guide to Types of Validity Psych.
📖 Next read:
- Reliability in Psychology: Understand how psychologists measure consistency and replicate results across studies.
- While randomisation ensures fairness, Operationalisation guarantees clarity — both are vital for valid and reliable psychological experiments.
