Aims & Hypotheses (AQA A-Level Psychology): Revision Notes
Aims & Hypotheses
What are aims?
An aim provides a clear statement explaining why research is being conducted and what researchers intend to investigate. It establishes the overall purpose and focus of the study without making specific predictions about outcomes.
For example, a research aim might be "to investigate the effect of caffeine consumption on reaction times." This tells us exactly what the researcher wants to examine but doesn't predict what they expect to find.
A well-written aim should specify both what is being studied and what the study hopes to achieve, giving readers a clear understanding of the research's direction and purpose.
Aims are about the 'what' and 'why' of research - they set the stage for investigation without predicting specific outcomes.
Understanding hypotheses
A hypothesis is a specific, testable prediction about what researchers expect to discover in their study. Unlike aims, hypotheses make clear predictions that can be supported or contradicted by research findings.
Hypotheses serve as the foundation for statistical testing and help researchers determine whether their results are meaningful or could have occurred by chance.
Types of hypotheses
Experimental/alternative hypothesis
The experimental hypothesis (also called the alternative hypothesis) predicts that the independent variable will have a measurable effect on the dependent variable. It suggests that any differences observed will be beyond what could reasonably be attributed to chance factors.
This type of hypothesis incorporates the expectation that results will be statistically meaningful. For instance, "caffeine consumption will have a notable effect on reaction times" predicts that the independent variable (caffeine) will produce measurable changes in the dependent variable (reaction times).
Statistical tests help determine whether research findings support the experimental hypothesis by showing the results are unlikely due to random chance.
Null hypothesis
The null hypothesis represents the position of "no effect" or "no difference." It predicts that the independent variable will not influence the dependent variable in any meaningful way, and any observed differences will be due to chance factors rather than the manipulation being studied.
Using the same example, a null hypothesis might state "there will be no notable difference in reaction times as a result of caffeine consumption." This assumes that caffeine has no real impact on the measured outcome.
Researchers use statistical analysis to determine whether they can reject the null hypothesis in favour of the experimental hypothesis, or whether the null hypothesis should be retained.
Directional vs non-directional hypotheses
Experimental hypotheses can be further classified as either directional or non-directional, depending on how specific their predictions are.
Directional (one-tailed) hypothesis
A directional hypothesis makes a specific prediction about which direction the results will go. It not only predicts that there will be a difference, but also specifies whether that difference will be an increase or decrease.
Directional Hypothesis Example
"There will be a notable reduction in reaction times as a result of caffeine consumption"
This predicts both that caffeine will have an effect AND that this effect will be a reduction (improvement) in reaction times.
Researchers typically use directional hypotheses when previous research provides strong evidence suggesting results will go in a particular direction, or when replicating studies that used directional predictions.
Non-directional (two-tailed) hypothesis
A non-directional hypothesis predicts that there will be a difference between conditions but does not specify the direction of that difference. It acknowledges that the independent variable will have an effect whilst remaining open about whether this will be positive or negative.
For instance, "there will be a notable difference in reaction times as a result of caffeine consumption" predicts an effect without specifying whether reaction times will become faster or slower.
Non-directional hypotheses are appropriate when researchers expect an effect but cannot confidently predict its direction, or when exploring new areas where previous research provides limited guidance.
Key Points to Remember:
- Aims explain what researchers want to investigate, while hypotheses make specific testable predictions about expected outcomes
- The experimental/alternative hypothesis predicts a measurable effect, while the null hypothesis predicts no meaningful difference
- Directional hypotheses specify the direction of expected results, whilst non-directional hypotheses predict differences without specifying direction
- Statistical testing helps determine which hypothesis is supported by the research findings
- The choice between directional and non-directional hypotheses depends on existing research evidence and the specific research context