Scientific inquiry utilizes two distinct types of hypotheses to ensure objectivity: the Null Hypothesis () and the Alternative Hypothesis ( or ).
Null Hypothesis (): This is the default position that assumes there is no significant relationship or difference between the variables being studied. It states that any observed effect is due to chance.
Alternative Hypothesis (): This is the researcher's actual prediction. It states that there is a significant relationship or difference caused by the manipulation of the independent variable.
It is critical to distinguish between a general research aim and a formal hypothesis. An aim is a broad statement of intent, while a hypothesis is a specific, directional prediction.
| Feature | Null Hypothesis () | Alternative Hypothesis () |
|---|---|---|
| Assumption | No effect / No difference | Significant effect / Difference |
| Purpose | Baseline for statistical rejection | The researcher's prediction |
| Outcome | Accepted if results are non-significant | Accepted if results are significant |
Check for Both Variables: Always ensure your written hypothesis explicitly names both the Independent Variable (the cause) and the Dependent Variable (the effect).
Use Comparative Language: A strong alternative hypothesis often uses words like 'more', 'less', 'higher', or 'lower' to indicate the direction of the predicted difference between conditions.
Verify Measurability: Ask yourself, 'Can I put a number on this?' If the dependent variable is 'happiness' or 'intelligence', it must be operationalized into a score or scale to be valid.
The 'No Difference' Rule: When writing a null hypothesis, always start with the phrase 'There will be no significant difference...' to ensure you are meeting the formal requirements.
Vagueness: Using subjective terms like 'better' or 'worse' without defining the metric of measurement makes a hypothesis untestable.
Circular Reasoning: Formulating a hypothesis that is true by definition (e.g., 'People who exercise more will be more physically active') provides no new scientific insight.
Confusing Correlation with Causation: A hypothesis for an experiment must predict that the IV causes the change in the DV, not just that they happen at the same time.
