Research Methods

Normative Social Influence - Behaviour to fit in with the group and avoid ridicule – an example of compliance.
Informational Social Influence - Most likely to occur when:
- Situation is ambiguous
- A situation is in crisis
- We believe others to be experts

Deception
Right to withdraw
Informed Consent
Protection from harm
Privacy and Confidentiality

Right to withdraw
We must make participants aware that they are free to leave a study at any time.
They can also refuse permission for their data to be used

Not everyone is capable of giving informed consent
We need to take special care when studying vulnerable people who may not understand the implications of taking part in a study

Confidentiality
Information about our participants is protected by the Data Protection Act
They must not be identifiable in published research
Participants are given numbers or referred to by a code or their initials

Repeated Measures Design
Participants take part in both conditions of the experiment

Limitations
- Order effects (e.g. practice effect, fatigue effect, recognising demand characteristics) as participants take part in all conditions.

Strengths
- There are no order effects as participants only take part in one condition so cannot get better through practice, or under-perform due to fatigue, or change their behaviour due to demand characteristics.
- It allows task variables to be controlled for example participants can be given the same word list in each condition so that this does not become a confounding variable.

Matched Pairs Design
Participants are matched in each condition for characteristics that may have an effect on their performance. e.g. A memory test

Limitations
- It is time consuming and expensive to match up participants

If your sample is representative then you can generalise the results of your study to the wider population.

Random Sampling
This is a sampling technique which is defined as a sample in which every member of the population has an equal chance of being chosen. This involves identifying everyone in the target population and then selecting the number of participants you need in a way that gives everyone in the population an equal chance of being picked.

An experiment is a research method used by psychologists which involves the manipulation of variables in order to discover cause and effect.
It differs from non-experimental methods in that it involves the deliberate manipulation of one variable, while trying to keep all other variables constant

Strengths
- High degree of control
- Replication of procedures is easy
- Cause and effect: The relationship between the IV and the DV should be easy to determine as long as the experiment is well designed.

Field
An experiment performed in the natural environment of those being studied.

Limitations
- Less control over extraneous variables
- Replication is difficult
- Time consuming and expensive

Strengths
- High ecological validity
- Lack of direct intervention by experimenter

Directional Hypothesis
Also known as a one-tailed hypothesis
States the expected direction of your results
(It will say which group will do better)

Independent Variable
What is being manipulated

Extraneous Variables
A variable which may interfere with the dependent variable

Aims
What is the researcher intending to investigate

Null Hypothesis
- Often states that there is no relationship between the variables in the study
- Your results will either backup your null hypothesis or it won't
- If your results don't then you reject it and go with your experimental hypothesis

Mean
The Average
Add up all the numbers and divide by the number of numbers

Limitations
- It is affected by extreme scores and can misrepresent the numbers as a result
- It can only be used with certain types of data

Strengths
- It can be used with nominal data

Median
Central Value
Calculated by arranging scores in order and finding the mid point

Limitations
- Not as sensitive as the mean as not all values are reflected

Strengths
- Easy to calculate

Standard Deviation
Measure of the spread of data around the mean.
Higher the value the more variation in your scores

Limitations
- Unduly affected by extreme scores
- More complicated to calculate

External Reliability
Measures consistency from one occasion to another