Aim
An aim identifies the purpose of the investigation. It is a straightforward expression of what the researcher is trying to find out from conducting an investigation. The aim typically involves the word “investigate” or “investigation”. It should also include the IV and DV if the research method is an experiment.
For example:
o To investigate the capacity of Short Term Memory using a digit span technique.
Hypotheses
A hypothesis (plural hypotheses) is a precise testable statement of what the researchers predicts will be the outcome of the study. This usually involves proposing a possible relationship between two variables: the independent variable (what the researcher changes) and the dependant variable (what the research measures).
For example:
o To investigate the effect of alcohol on a person’s ability to remember words.
In order to write a hypothesis you need to identify the key variables in the study (IV & DV).
For example, if your study was to investigate the affect alcohol has on word remembered, then your IV is the amount of alcohol consumed and the DV is the number of words remembered.
Your hypothesis could be:
o There will be a relationship between the number of words remembered and the amount of alcohol consumed. (Two Tailed)
Or
o The more alcohol consumed the less the words will be remembered. (One Tailed)
Aim and Hypothesis Example
So, for a psychologist who wants to find out whether or not television influences gender-role stereotypes held by teenagers.
The aim of the research could be:
o “An investigation into the effects of television on the gender role stereotypes of teenagers.”
This is a general statement of interest.
The hypothesis, on the other hand, must make a prediction concerning how television may influence gender-role stereotypes. For example:
o “Teenagers who regularly watch Eastenders will see males as more aggressive than females, compared with teenagers who rarely, if ever, watch Eastenders”.
Alternative and Null Hypotheses
In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, or Hn, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment), or Ha or He (either shorthand version is acceptable). Briefly, the hypotheses can be expressed in the following ways:
o The Hn states that there is no relationship between the two variables being studied (one variable does not affect the other).
o The Ha states that there is a relationship between the two variables being studied (one variable has an effect on the other).
A research hypothesis (Ha) prediction is one that states that results are not due to chance and that they are significant in terms of supporting the idea being investigated. A 'null hypothesis' (Hn) prediction is one that states results are due to chance and are not significant in terms of supporting the idea being investigated.
In order to write the Ha and Hn for an investigation, you need to identify the key variables in the study. A variable is anything that can change or be changed, i.e. anything which can vary. Examples of variables are intelligence, gender, memory, ability, time etc.
Let’s consider a hypothesis that many teachers might subscribe to: that students work better on Monday morning than they do on a Friday afternoon (IV=Day, DV=Standard of work). Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and on a Friday afternoon and then measuring their immediate recall on the material covered in each session we would end up with the following:
o The experimental hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
o The null hypothesis states that these will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.
The null hypothesis is, therefore, the opposite of the experimental hypothesis in that it states that there will be no change in behaviour.
At this point you might be asking why we seem so interested in the null hypothesis. Surely the alternative (or experimental) hypothesis is more important?
Well, yes it is. However, we can never prove the alternative hypothesis. What we do instead is see if we can disprove, or reject, the null hypothesis. If we can’t reject the null hypothesis, this doesn’t really mean that our alternative hypothesis is correct – but is does provide support for the alternative / experimental hypothesis.
One-Tailed and Two-Tailed Hypotheses
The experimental (alternative) hypothesis can directional or non-directional:
Sometimes a hypothesis predicts the direction in which the results are expected to go. For example, “studying significantly improves exam marks”; “Women are significantly better drivers than men”. When hypotheses predict the direction of the results like this they are known as one-tailed (or directional) hypotheses.
If a hypothesis does not state a direction but simply states that one factor will affect another, or that there will be a difference between two sets of scores (without saying which direction that difference will be) then it is known as a two-tailed (or non-directional) hypothesis. For example, “anxiety influences performance”; “there is a significant difference in the driving performance of men and women”.
You must make sure that you can recognise whether a hypothesis is 1 or 2 tailed as this has serious implications for how you interpret your data
Just to recap:
- A one-tailed hypothesis states the direction in which the results are expected to go (i.e. in one direction). E.g. “boys will recall more words than girls”.
- A two-tailed hypothesis does not give a predicted direction. E.g. “there will be a difference in the number of words girls and boys recall”.