When carrying out a piece of research it is essential that you have an aim in mind.  This needs to be reasonably precise, for example ‘I’m gonna study memory’ would not be sufficiently precise.  However the aims are broader, or less precise than the hypotheses.  A suitable aim for memory might be ‘to see if age affects the duration of STM.’

Science should also be objective. This means not letting personal (subjective) opinions affect the data. When a study has strong controls, objectivity and operationalised variables(measurable concepts), the results
should be replicable. They can be shown to be reliable by repeating the study to find similar results.
It the results are reliable and support the hypothesis, the theory is supported by the study. Otherwise, the theory has to be amended, or abandoned, should the results show the theory as false. Then further hypotheses are generated.


A variable is anything which is likely to affect the experiment. The independent variable (IV) is the variable which is changed or manipulated by the experimenter. This is to see what effect it has on the dependent variable (DV). This is what is being measured by the researcher. The DV changes as the experimenter manipulates the IV. Both of these variables must be measurable, this means operationalising them (see below). An extraneous variable is any other variable which affects the results. Experiments have strong controls to decrease the number of extraneous variables,which affect the results as well as, or instead of, the IV. There are two main extraneous variables:

  • participant variables – for example age, gender, experience and mood of the participants
  • situational variables – for example temperature, background noise, interruptions and lighting conditions

Extraneous variables should be controlled, but any which are not controlled and affect the results are called confounding variables. These are explained in more detail in a later lesson.

Experimental Hypotheses

An operationalised hypothesis is more precise and shows how the variables will be measured. The experimental hypothesis can make your prediction, for example:

As age increases the duration of STM decreases.’

When deciding on an experimental hypothesis you need to give some indication of the method to be used.  For the above experiment it might be: ‘Duration of STM, as measured by the Brown-Peterson technique, will decrease with age.’

Having decided on your hypothesis and aims you need to decide on the direction. This will depend on whether previous research indicates in which direction the independent variable will affect the dependent. If previous research indicates an expected result, then your hypothesis will be directional. If you are simply looking to see how one variable affects the other, but are unsure as to what you will find, your hypothesis would be non-directional.

For example:

Directional: “As age increases the duration of STM decreases”

When we say that we expect ‘duration of STM to decrease as age increases’ we are making a definite prediction.  That prediction has direction. You could predict this with some confidence since all past research suggests that this is the case.

Note: Directional/non-directional does not apply to the null hypothesis.  These will always read, “not be affected” or “no correlation” etc.


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