# Aims and Hypotheses

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### Aims

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”.

For example:

• Milgram (1963) investigated how far people would go in obeying an instruction to harm another person.

• Bowlby (1944) investigated the long-term effects of maternal deprivation.

## Types of Hypotheses

A hypothesis (plural hypotheses) is a precise, testable statement of what the researchers predict 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).

In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment).

Briefly, the hypotheses can be expressed in the following ways:

• The null hypothesis states that there is no relationship between the two variables being studied (one variable does not affect the other). It states results are due to chance and are not significant in terms of supporting the idea being investigated.

• The alternative hypothesis states that there is a relationship between the two variables being studied (one variable has an effect on the other). It states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.

In order to write the experimental and null hypotheses 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.

A good hypothesis is short and clear should include the operationalized variables being investigated.

### For Example

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:

• The experimental hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.

• 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 behavior.

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 100% 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 it does provide support for the alternative / experimental hypothesis.

## One tailed or two tailed Hypothesis?

A one-tailed directional hypothesis predicts the nature of the effect of the independent variable on the dependent variable.

• E.g.: Adults will correctly recall more words than children.

A two-tailed non-directional hypothesis predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified.

• E.g.: There will be a difference in how many numbers are correctly recalled by children and adults.