Types of Experiment

Lab experiment: conducted in a controlled environment, allowing the establishment of causality. It uses standardised procedure and pp's are randomly allocated to experimental groups.

Advantages

• high degree of control - IV and DC are operationalised
• replication - can be easily repeated to check results
• cause and effect - effect must come from manipulation of the IV as all other variables are controlled
• isolation of variables - lab means individual pieces of behaviour can be isolated and tested

Disadvantages

• experimenter bias - expectations can affect results
• problems operationalising IV and DV - can become too specific and not relate to wider behaviour
• low external (ecological) validity - high degree of control = artificial and unlike real life
• demand characteristics - as pps are aware they are being tested

Field Experiment: conducted in a naturalistic environment where the researchers manipulate the independent variable

Natural experiment: the independent variable varies naturally

Quasi experiment: researcher is unable to freely manipulate the IV or randomly allocate pps to different conditions

Advantages:

• high ecological validity - results relate to everyday behaviour and can be generalised
• no demand characteristics - often pps are unaware of the experiment

Disadvantages

• less control - causality is harder as it is more difficult to control extraneous variables
• replication - difficult to exactly repeat field experiments
• ethics - lack of informed consent

Observations involve watching and recording behaviour in naturalistic, real-world settings.

There are 2 main types of observation:

• Participant observation - observers actively become involved in the situation, eg Zimbardo
• Non-participant observation - researchers do not become actively involved, eg Ainsworth

Observations can also be:

• Overt - participants are aware they are being observed
• Covert - participants are UNaware they are being observed.

Advantages

• high external validity - observations occur in natural settings = behave naturally + behaviour can be generalised to other settings
• practical methods - deliberate manipulation of variables would be unethical/impractical
• few demand characteristics - in covert observations

Disadvantages

• cause and effect - causality cannot be inferred since the variables are only observed, not manipulated, and there is little control over extraneous variables
• observer bias - observers may see what they want to see. This can be reduced using inter-observer reliability
• replication - lack of control over variables means conditions can never be repeated exactly to check results
• ethics - if pps are unaware of being observed, there are issues of invasion of privacy and informed consent

There are several ways in which data can be gathered from naturalistic observations. The development of effective behavioural coding categories is important to the success of observational studies.

Behavioural categories: dividing target behaviours into subsets of behaviour using code systems. Observers agree on a grid/coding sheet

Sampling procedures:

• event sampling - counting the number of times a behaviour occurs
• time sampling - counting behaviour in a set time frame, eg every 30 seconds

Inter-observer reliability: observers constantly code behaviours in the same way. This lessens the chances of observer bias.

Self-report techniques: these are research methods in which participants give information about themselves without researcher observation

Questionnaires: a self-report method where participants record their own answers to a pre-set list of questions.

There are 2 main types of questions asked:

• closed (fixed) questions - involves yes/no answers
• open questions - allow participants to answer in their own words

Advantages

• quick - large amounts of info can be gathered quickly
• lack of investigator effects - can be completed without a researched present
• quantitative and qualitative analysis - closed questions = easy to analyse and open = further detail
• replication - standardised questions are used = easy to replicate

Disadvantages

• misunderstanding - pps may misinterpret questions
• biased samples - questionnaires are suitable for people who have time to fill them out = may not be representative of the whole population
• low response rates - uneconomical research method as they get very low return rates
• superficial rates - closed questionnaires are not suitable for sensitive issues
• social desirability/idealised answers - people may lie and give answers they think are expected of them

Aims - this makes it easier to write questions that address a purpose

Length - should be short and to the point

Previous questionnaires - shows what was previously successful

Question formation - should be concise, unambiguous and easily understood

Pilot study - questionnaires should be tested on people who can provide detailed and honest feedback

Measurement scales - can be used to assess psychological characteristics or attitudes (Likert scale)

Interview: a self-report method where participants answer questions in face to face situations.

3 main types of interview:

• structured - identical closed questions, interviewer writes down the answer, does not require much training
• unstructured - informal discussion, can explore interesting answers using follow-up questions, needs considerable training
• semi-structured - combining structured and unstructured techniques, producing both quantitative and qualitative data

Design of interviews: several interpersonal variables affect the decision of who would make a suitable interviewer:

• gender and age - can affect sexually sensitive answers
• ethnicity - misunderstandings and difficulties
• personal characteristics and adopted role - interviewers can change accent and appearance

Advantages:

• complex issues - sensitive issues can be dealt with in person, pps can be relaxed especially in unstructured interviews
• ease misunderstandings - questions can be explained
• data analysis - semi-structured produces both quantitative and qualitative, structured produces quantitative
• replication - the more standardised/structured, the easier it is to replicate

Disadvantages

• interviewer effects - interviewers may unconsciously bias answers, demand characteristics, social desirability bias
• interview training - a lot of skill is required to carry out unstructured interviews
• ethical issues - pps may not know the true purpose of an interview
• participant answers - some may find it difficult to express feeling/opinions

Correlational studies - measuring the strength and direction of relationships between co-variables. +ve correlation - when one co-variable increases the other increases                                                 -ve correlation - when one co-variable increases the other decreases                                                 Scattergraphs are used to display the extent to which two co-variables are correlated

Advantages:

• allows predictions to be made
• allows quantification of relationships - correlations show a relationship
• no manipulation - correlations do not require manipulation of variables

Disadvantages:

• quantification problem - high correlations are not always statistically significant
• cause and effect - correlations are not under controlled conditions so do not show causality
• extraneous variables
• only works for linear relationships

Correlational studies - measuring the strength and direction of relationships between co-variables. +ve correlation - when one co-variable increases the other increases                                                 -ve correlation - when one co-variable increases the other decreases                                                 Scattergraphs are used to display the extent to which two co-variables are correlated

Advantages:

• allows predictions to be made
• allows quantification of relationships - correlations show a relationship
• no manipulation - correlations do not require manipulation of variables

Disadvantages:

• quantification problem - high correlations are not always statistically significant
• cause and effect - correlations are not under controlled conditions so do not show causality
• extraneous variables
• only works for linear relationships