Formulating Hypotheses

Research in psychology begins with a question or an observation about human behaviour. Before conducting any study, psychologists must formulate clear, testable statements about what they expect to find. These statements are called hypotheses.

What is a Hypothesis?

A hypothesis is a clear, testable, predictive statement about the expected outcome of a study. It is not a question — it is a statement that can be tested through research and either supported or refuted by the evidence.

Characteristics of a Good Hypothesis

Testable — it must be possible to design a study to test it
Specific — it must clearly state what is being measured and what the expected outcome is
Operationalised — the variables must be defined in measurable terms

Types of Hypothesis

1. Alternative Hypothesis (Experimental Hypothesis)

The alternative hypothesis (H₁ or Hₐ) states that there will be a difference, relationship, or effect. This is what the researcher expects to find.

There are two forms:

Directional (one-tailed) hypothesis — predicts the direction of the difference or relationship:

Example: "Participants who revise using spaced practice will score higher on a memory test than participants who use massed practice"

Non-directional (two-tailed) hypothesis — predicts that there will be a difference but does not specify the direction:

Example: "There will be a difference in memory test scores between participants who use spaced practice and those who use massed practice"

2. Null Hypothesis

The null hypothesis (H₀) states that there will be no difference, relationship, or effect — any observed difference is due to chance.

Example: "There will be no significant difference in memory test scores between participants who use spaced practice and those who use massed practice. Any difference is due to chance."

When to Use Directional vs Non-Directional Hypotheses

Type	When to Use	Example
Directional	When previous research or theory suggests a clear direction for the result	"Students with growth mindset will score higher..."
Non-directional	When the area is under-researched or previous findings are contradictory	"There will be a difference in scores..."

Operationalisation of Variables

Operationalisation means defining variables in a way that can be measured and tested. Vague terms must be made specific.

Vague Term	Operationalised Version
"Memory"	Score on a 20-word recall test
"Anxiety"	Score on a standardised anxiety questionnaire (e.g. State-Trait Anxiety Inventory)
"Intelligence"	Score on a standardised IQ test
"Aggression"	Number of aggressive acts observed in a 10-minute period

Exam Tip: Always operationalise variables in your hypotheses. Instead of "Stress affects memory," write "Participants who complete a stressful task (giving a speech to strangers) will recall fewer words from a 20-word list than participants who complete a non-stressful task (reading quietly)."

Aims vs Hypotheses

An aim is a general statement of what the study intends to investigate. A hypothesis is a specific, testable prediction.

Feature	Aim	Hypothesis
Specificity	General	Specific and testable
Example	"To investigate whether sleep affects memory"	"Participants who sleep for 8 hours will recall more words from a 20-word list than participants who sleep for 4 hours"

Key Points

A hypothesis is a clear, testable, predictive statement.
Alternative hypothesis: predicts a difference or effect (directional or non-directional).
Null hypothesis: predicts no difference — any result is due to chance.
Variables must be operationalised — defined in measurable terms.
Aims are general; hypotheses are specific and testable.