Research Methods Booklet -TES Version

7/29/2019 Research Methods Booklet -TES Version

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TOPIC 3 (Unit 1)

RESEARCH METHODS

An Intro to the Topic

What are Research Methods?

All of us have our own personal theories about why people

think and behave in the ways they do. However,

psychologists differ from lay people in that they develop

scientific theories, which they then test by carrying out

carefully designed research studies. The main methods

used by psychologists to carry out their research include

experiments, correlation techniques, observational

techniques, case studies and self-report techniques

including interviews and questionnaires. Psychologists use

research methods to gather and make sense of the data

they produce.

SECTION 1:

Research Methods and Techniques:

Area of Specification Being Covered:

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Research Methods: (i) Methods and Techniques, candidates will beexpected to demonstrate knowledge and understanding of the following research

methods, including their advantages and weaknesses:

Experimental method, including laboratory, field and naturalexperiments.

Studies using correlational analysis.

Observational techniques

Self-report techniques including questionnaire and interview.

Case studies

TIP: remember that all that you learn in research methods informs your critical thinking in relation to everythingelse you study in psychology. When you are evaluating a theory you should look to the evidence that supports the

theoryuse your knowledge of research methods to judge the credibility of the evidence offered. This willsignificantly enhance your use of analytic and evaluative skills.


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Research Methods and Techniques:

1) What are experimental methods?

Experimental methods provide the most precise way of testing hypotheses

because they seek to establish cause and effect relationships. A true

experiment has three key features:

1. Manipulation of the independent variable: the independent variable

(IV) is directly manipulated to produce a change in the dependent

variable (DV).

2. Randomisation: a true experiment requires that

participants are randomly allocated to conditions or thatthe participants take part in each condition of the

independent variable.

3. Control: All variables other than the IV and DV need to

be controlled in an experiment. These other variables are known as

extraneous variables (EVs), the aim is to minimise the impact of

these variables on the results of the investigation.

NOTE: Where EVs are important enough to impact on the results

of a study these variables become Confounding Variables.

One way to ensure control within an experiment is to have a control group.

This is the group of participants who do not receive the experimental

treatment or condition so that they can act as a comparison to the

participants who do.

What are the different types of experiments?

A) Laboratory Experiment:

A laboratory experiment is an experiment that is carried out in a

controlled environment, its typical features include:

Direct manipulation of the independent variable.

Control of all other extraneous variables.

Participants are randomly allocated to conditions.

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Pgs 106-107


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(ii) Advantages and disadvantages of Lab experiments:

Advantages: High levels of control, both the IV and Evs are controlled,

therefore easy to establish cause and effect. Easy to replicate- which means it is easy to ensure that the

results are reliable as study can be replicated. This may also

mean that it could easily be applied to different groups of

people particularly to other cultures/ settings increase the

population validity of the study.

Disadvantages: Laboratory experiments lack ecological validity as they do not

approximate real life situations. High chance of investigator and participant effects (demand

characteristics). This means that the internal validity of the

study may be compromised as people may behave differently

(consider screw you effect).

They lack mundane realism (situations are very artificial),

therefore results cannot always be generalised to other

situations.

An example of a lab experiment is Ainsworths strange situation.

B) Field Experiment:

A field experiment is an experiment that takes place in a natural

environment. The typical features of field experiments include:

a. Direct manipulation of the independent variable.

b. Participants are not necessarily randomly

allocated to conditions.

(ii) Advantages and disadvantages of field experiments:

Advantages: Can conclude cause and effect.

Higher levels of ecological validity than lab experiments, which

means that results can be applied to real life conditions.

Reduced demand characteristics, which means that internal

validity is not compromised.

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Disadvantages: Field experiments have less control over extraneous variables,

so it will be harder to establish cause and effect compared to

Lab experiments. Often more time consuming than laboratory experiments, which

means that they will be harder to replicate.

Random allocation to conditions is difficult.

An example of a field experiment is that by Hofling et al (1966) who

studied obedience levels in nurses.

C) Natural Experiment:

A natural experiment is a quasi- experiment, where the researcher

takes advantage of a naturally occurring variable. The typical features

of natural experiments include:

a. A Natural occurring independent variable (NOT controlled by

researcher).

b. No random allocation of participants to conditions

(ii) Advantages and disadvantages of natural experiments:

Advantages:

Useful where it is unethical or impossible to manipulate the

independent variable.

High levels of ecological validity which means that results can be

applied to real life scenarios.

Disadvantages:

Problems with internal validity as many extraneous variables cannot be

controlled therefore cause and effect cannot be established. There is no random allocation to conditions.

Low control over the experiment (therefore reliability and validity may

be compromised).

An example of a natural experiment is that by Campbell et al (2000)

who looked at the effects of day-care on sociability in children.

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TIP: You should learn at least two advantages and two disadvantages of the different experiments. Remember that if

two or three marks are available then mere identification of the advantage/ disadvantage would only gain you one

mark; you need to elaborate to gain full marks.

E.G. if claiming that lab experiments lack in ecological validity you would gain 1 mark, for more marks you wouldneed to elaborate and state that this is due to the artificiality of the situation and that as a result of the low ecological


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2)Studies using correlational analysis:

What is meant by correlation?

A correlation refers to the measurement of a relationship between

two or more variables. The variables measured are known as co-

variables.

There are two types of correlations:

A) Positive correlation:As one variable increases so does the other variable, for

example as the level of secure attachment increases thenumber of smiles a child gives also increases.

B) Negative Correlation:As one variable increases the other variable decreases, for example, as

the number of hours spent in day care increase, the less

cooperative children were.

(ii) Recognising and measuring correlations:Correlational relationships are identified and demonstrated through the

use of statistical techniques. This means that the variables need to be

operationalised, that is given a numerical value.

Using the example above, the amount of time children spend in day care is

quantitative as it can be measured in hours/ days/ weeks. However, the

amount of cooperation they display cannot be counted in any form of

measurement, so they would need to be operationalised by scoring them on

a rating scale, eg: 1 = no pro-social behaviour and 10= extreme pro-social

behaviour. Correlational studies rely on quantitative data because they

measure the strength and direction of the relationship between two

variables.

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Pgs 116- 117


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(ii) Correlation Co-Efficients:

A correlation co-efficient is a numerical representation of the strength

and direction of the relationship between two variables. A correlation

coefficient can range between -1.0 and +1.0. The number indicates thestrength and of the relationship ie- the extent to which the variables are

related.

The sign + or indicates the direction of the relationship and

whether the correlation between the variables is positive (+) or

negative (-) .

+1 indicates a perfect positive correlation as shown in the graph

above and -1 a perfect negative correlation as shown above. 0 means

there is no correlation.

The nearer the number is to +1 or -1, the stronger the correlation!

E.G. +0.7 would mean a strong positive correlation, whereas -0.8

would be a strong negative correlation (+0.2 would be a weak positive

correlation and -0.22 would be a weak negative correlation).

NOTE: you will not be asked to calculate a correlation

coefficient, only to interpret it

(iii) Using correlational analysis has advantages and

disadvantages:

The advantages of using a correlational study are:

They can establish a relationship between two variables.

They allow researchers to statistically analyse situations that

could not be manipulated experimentally for ethical orpractical reasons (e.g. the relationship between time spent in daycare and sociability in children).

The disadvantages of using a correlational study are:

Correlation does not establish cause and effect; it only

establishes a relationship between two variables. There may

be a third variable that has not been identified that is

creating the relationship.

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For example, in the relationship between stress and illness, it may not be that stress causes illness but insteadthat people under stress have less healthy lifestyles and it is this which in turn causes the illness.


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Disadvantages continued

Correlations only identify linear relationships not curvilinear.

3) Observational techniques:

What are observational methods?

The observations in a scientific study will focus precisely on particular categories

of behaviours or events. Secondly, these observations would be part of a research

plan that would include clear operational definitions of the behaviours or events to

be observed. It is also likely that a hypothesis would have been formulated to

guide the observationsthis is a sharp contrast to casual observations when we

often find ourselves people watching.

Observational methods can be used for data collection within

experiments as well as in purely observational research. The type ofobservation used will depend largely upon the investigation and

whether the latter is based on a true experiment (with manipulation

of the IV) or not.

What are the different types of observations?

There are two main types of observations, these are Naturalistic

observations and Controlled observations.

Naturalistic Observations:

These are observations where the researcher observes naturally occurring

behaviours. This type of observation cannot be used in a true experiment

where the researcher manipulates the independent variable to observe the

effect on the dependent variable. However, naturalistic observations can

be used in quasi-experiments such as natural experiments.

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For example, the relationship between temperature and aggression is a curvilinear

relationship. The relationship between temperature and aggression is only positive

up to a point, since at very high temperatures aggression begins to decrease.

Pgs 112-114


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Controlled observations:

These are observations where the researcher attempts to control certain

variables. Controlled observations can be carried out in a laboratory, a good

example is Ainsworths strange situation (1970), where children were studied

under laboratory conditions where she could control all other variables andobserved how infants reacted to separation from their mother.

When discussing observations, further distinctions can be made along three main

dimensions:

i) Participants V non-participant observation.

Participants observation requires the researcher to actually join the group or

take part in the situation they are studying. On the other hand, non-

participant observation, is when the researcher observes from the outside or

from a distance.

ii) Disclosed (or overt) and undisclosed (or covert)

observation

A disclosed observation is an observation in which the participants

are aware that they are being observed. Alternatively, undisclosed

observations are observations in which the participants are

unawarethat they are being observed.

iii) Structured and unstructured observations

A structured observation is where the researcher has already determined

precisely what behaviours are to be observed and will use a standardisedchecklist to record the frequency with which those behaviours are observed

within a specified period of time. Unstructured observations on the other

hand, follow no checklist and the researcher will simply record anything he/

she finds interesting or relevant to the study.

(ii) Using observational methods has advantages anddisadvantages:

A major problem faced by observational studies is observer bias. This happenswhen an observer makes their own particular interpretation of the behaviour they

observe. People can interpret behaviour differently according to expectation and

social stereotypes. As a result, if an observer is expecting to see something, then

their observations may be biased to the extent that they find it in what they see.

This bias would affect the overall reliability of the research. To prevent this,

some strategies can be used, such as the use of double blind techniques,

where the observer (who acts on behalf of the researcher) and the

participants are both unaware of the hypothesis being tested.

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See table below for the advantages and disadvantages associated with

each type of Observation!

Type of

observation

Advantages Disadvantages

Naturalistic High levels of ecological validity.

Participants may be unaware that they are being

observed and therefore they may behave more

naturally.

No control over E.Vs

If the participant is unaware that they are

observed, then this may raise ethical issue

lack of informed consent.

Controlled Higher levels of control over E.Vs Participants may be affected by the factthey are being observed.

Behaviour may not be natural; this impacts o

ecological validity of the research.

Participant Very high ecological validity

Rich qualitative data can be collected by the

research (consider general advantages of this type ofdata)

Easier to understand what the observees

behaviour actually means.

A relationship based on trust can be established

between those being observed and the observer.

The researcher has to rely on memory ascannot take notes (unreliable).

Observer may become too emotionally inv

with the observees, meaning that observ

can become subjective rather than objective.

The presence of the observer may chang

group dynamics.

Non-

participant

Observees may not realise that they are being

observed meaning that behaviour may not be

changed by the presence of the observer.

The observer may be more objective as they are

less likely to become emotionally involved with

the participants.

The observer can record their observations as

they occur making them more reliable in terms of

memory.

The actual meaning of the behaviour may n

so clear from a distance.

A relationship is not formed between

observer and the observee with the conseq

that there may be less trust.

Disclosed

observation

Reduction of ethical issues- the observee knows

they are being observed and thus has given their

consent to the researcher doing so.

Increases the trust between researchers and

the public

Increase in reactivity as the observee may c

their behaviour as they know they are

observed. There will be an increase in de

characteristics.

Undisclosed

observation

Reduction of reactivity as the participant does

not realise they are being observed, meaning that

there are less demand characteristics.

Ethical issues raised about the observation (eg co

When the observee realises they have been obs

they may come to distrust psychologists in future.

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IP: You may be asked to identify two factors that could affect the validity of an observation. For this focus on confounding variables thatould affect the research orobserver bias (explain what this is- Observer bias can also reduce the reliability of the data, you would need touggest ways in which observer bias could be reduced.) You could also focus on the positive aspects, such as naturalistic observations being

gh in ecological validity because the behaviour is occurring in a natural environment.


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4 ) Self report techniques including questionnaires (or

surveys) and interviews.

Questionnaires:

A survey or questionnaire involves asking a large

sample of people for information on specific topics

and specific moments in time. The questionnaire

places a lot of emphasis on selecting a representative

sample of participants. This is because the researcher

will want to make generalisations about their findings

that is that the findings obtained will also apply to

the rest of the population being looked at. When

designing questionnaires, there are a few keyconsiderations to be taken into account. These involve:

Type of questions: open or closed questions.

Open questions allow respondents to answer in full and produce

qualitative data eg: What are your views on

Closed questions are fixed choice questions and require participants

to choose an answer from a list provided eg: Do you use the internet?

YES/ NO/ Sometimes

Ensure that questions and instructions are easy and simple to follow.

Keep the amount of information asked for to a minimum- only

questions directly related to the research need to be asked, if

asking for age and gender, then this would have to tie in with the

research somehow.

Ethical considerations- ensure that questions asked are not invasive

or inappropriately personal questions.

Pilot studies may be needed and where appropriate changes would be

made.

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Pgs 118-120


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What are the advantages and disadvantages of using

Questionnaires/ survey methods?

Advantages/ strengths:

Open ended questions can provide rich and detailed qualitative data,

they allow the respondent to express what they really think and are

much more realistic (consider advantages of qualitative data here

too).

Closed questions provide quantitative data which can be statistically

analysed and are therefore less subject to bias interpretation.

Questionnaires can be used to question a large sample of people

relatively quickly- this can increase population validity if different

groups are targeted at once. They are easy to use and require no previous training.

Can be used to collect large amounts of data about what people

think as well as what they say they do.

The researcher does not have to be present while the participant

completes the questionnaire, which can reduce investigator effects

as there is a reduction in the influence of interpersonal factors eg:

answering in the way that the respondent thinks the researcher

wants the question to be answered, this judgement is often based

on looks/ age of researcher etc therefore if the researcher isnt

there, these effects are reduced.

Disadvantages/ Limitations:

Open ended questions that collect qualitative data can make the

data difficult to analyse and more prone to investigator bias.

Closed questions can be artificial and not realistic, reducing the

ecological validity of the data collected. In addition, it could be

unclear how the respondent has interpreted the question which in

turn may influence the overall validity and reliability of the

questionnaire.

Social desirability effects- people may give untruthful answers to

appear socially desirable, in particular with sensitive issues such as

parenting styles/ alcohol abuse etc. If the authenticity of the

responses cannot be guaranteed then the validity of the data is

seriously threatened!

Only those who can read and write can take part, therefore,

findings cannot be generalised to the entire population- consider

the effect on the population validity of the study, especially in

countries where literacy rates are low.

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Social

desirability:

The tendency ofhumans to present

themselves in thebest possible light.

There may be adifference in what

people say they doand what they

actually do!


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Difficulty phrasing questions clearly may result in different

interpretations of questions and therefore inaccurate responses

obtained (again consider reliability and validity issues here).

Interviews:

Interviews are an alternative method for asking

questions, they differ in their face-face nature. They are

particularly useful for gathering more detailed

information and enabling a more natural and flexible

approach. In interview methods, the interviewer normally

has a schedule or structure of topics they wish to

explore. Interviews can be structured to yield

quantitative data (similar to how this is done for

questionnaires) or unstructured to produce more

qualitative data.

What are the advantages and disadvantages of using

Interview methods?

Advantages/ Strengths:

Detailed information can be obtained (qualitative). This allows the

interviewer to clarify the meaning and significance of the

information being provided.

Allows the participant to freely express themselves.

Unstructured interviews may encourage participants to be honest

and this may raise new lines of research.

Disadvantages/ Limitations:

Statistical analysis can be difficult if the interview is unstructured

and the data collected is qualitative in nature. More time consuming than a questionnaire.

Greater chance of interpersonal variables affecting the responses

ie- increased risk of investigator effects.

Social desirability effects are increased as the interview takes

place face to face and the participant might not want the

researcher to view them in a negative light (Consider validity of the

data).

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TIP: In the exam you may be asked to construct a question that yields qualitative data, an easy way to do this is to ask an

open question beginning with explain or What are your views on

If asked to construct a question to yield quantitative data then limit the choices participants would have to answer thequestion and explain that you would then calculate how many people picked a particular choice (eg: Do you drink

alcohol? Often Sometimes Never).

Pg 121


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A case study is an in-depth study of one individual

or a group of people. The fact that it focuses on a

single case means that it is idiographic in nature.

Normally, a case study involves the production of acase in history. A case study can be longitudinal or

retrospective and by nature are individualistic,

case studies normally share the following features:

The method is descriptive and data

collected is qualitative.

Research is often very focused on a particular aspect of behaviour.

Genie, the case of the Czech twins, and the case of KF (cognition)

are examples of case studies we have looked at.

What are the advantages and disadvantages of case

studies?

Case studies provide an effective way of gaining insight into the personal

experiences of the person under study and for suggesting new avenues of

research. Although many scientists reject case studies claiming these are

not scientific, it is a very rich method that has been known to challenge

established thinking in psychology Eg: Genies case study challenged

established thinking that human beings could learn to talk even past a

certain age.

Advantages/ strengths: Produces rich meaningful data (qualitative, what are the advantages

of qualitative data?).

High in mundane realism/ ecological validity (Why exactly is this a

strength?).

Can challenge established thinking and lead to new psychological

insights.

Disadvantages/ Limitations: Difficult to replicate, therefore difficult to establish the reliability

of the data.

Due to their idiographic nature, it is difficult to generalise the

results beyond the individual or group being studied- low in

population validity.

The possibility of researcher bias is high, which further calls into

question its scientific credibility.SECTION 2:

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Investigation Design:


Intro to the topic:

The first steps in designing a research investigation involves identifying a

topic or issue to study and carrying out a search and review

of the existing or background literature on the area. When

these initial stages have been completed, the researcher is

in a position to identify the aim and hypothesis of their

investigation.

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Research Methods: (ii) Investigation Design candidates should be familiarwith the following features of investigation design/;

Aims

Hypotheses, including directional and non-directional.

Experimental design (Independent groups, repeated measures and

matched pairs)

Design of naturalistic observations, including the development and

use of behavioural categories.

Design of questionnaires and interviews

Operationalisation of variables, including independent and dependentvariables.

Pilot studies

Control of extraneous variables

Reliability and validity

Awareness of the British Psychological Society (BPS) Code of Ethics

Ethical Issues and ways in which psychologists deal with them

Selection of participants and sampling techniques, including random,

opportunity and volunteer sampling

Demand characteristics and investigator effects.


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What are the Aims of a study?

Research investigation always needs an aim to give it a clear focus. The

aim of a study is a general statement about the purpose of the

investigation.

EG- AIM: To investigate the relationship between stress and illness.

What is a hypothesis ?

A hypothesis is a precise, testable statement about the expected

outcome of an investigation. The hypothesis should be expressed as a

very specific statement or prediction about the outcome of theinvestigation. Usually, the hypothesis is based on some previous

observations, such as noticing how children at a nursery behave before

and after their morning snack break.

Investigations normally have two hypotheses to be tested:

The experimental hypothesis, that is the one predicting a relationship

between variables.

The null hypothesis, which states that there will be no relationshipbetween the variables being tested.

In addition, there is also the alternative hypothesiswhich refers to

any hypothesis which is not the null hypothesis. In addition, Alternative

hypotheses can be experimental at the same time, but this is not always

the case, where a hypothesis does not predict cause and effect it is an

alternative hypothesis but not an experimental hypothesis.

EXAMPLES:Experimental Hypothesis: Participants who read digits out loud will

later recall a greater number of digits than participants who read the

digits sub-vocally.

Null hypothesis: There will be no difference between the number of

digits recalled by participants who read digits out loud and those who

read them sub-vocally.

Alternative hypothesis: There will be an association between parenting

style and infant emotional development.

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Pgs 90- 91


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What is a directional and non-directional hypothesis ?

In addition, you also need to understand that an experimental and

alternative hypothesis can be directional or non-directional. Look at the

table below for definitions and examples of these:

Experimental/

alternative

hypothesis

Definition Example

Directional A directional hypothesis is more precise than a non-directional hypothesis and specifically states the

direction of the results. This is sometimes known as a

one-tailed hypothesis because it predicts the nature

or the direction of the outcome.

Participants who read digits o

later recall a greater number

than participants who read

sub-vocally.

(the direction is clearly statmore digits will be recalle

condition).

Non- directional A non-directional hypothesis is one in which thedirection of the results is not predicted. This is also

known as a two-tailed hypothesis because the

direction of the result is not specified but could go in

either direction- that is it could be more or less.

There will be a difference in t

of digits recalled in the readi

condition compared to the

condition

(the direction is not stated

hypothesis only states that th

a difference but it has not s

which condition more or less direcalled).

Null Hypothesis This tends to state that there will be no differencerelationship between the variables being

investigated. A null hypothesis is used because it

makes a very precise prediction (nothing will happen)

than can be easily disproved, thereby providing

evidence to support the alternative hypothesis.

There will be no differenc

number of digits recalled in t

out loud condition compared t

vocal condition.

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TIP: When asked to write or to identify a directional hypothesis look out for indicatorwords such as more, less, increased, decreased etc. These words all indicate a

direction to the results. Alternatively, words such as difference or affect indicate a non-

directional hypothesis, so you are saying there will be a difference but you havent stated inwhat direction the difference will be.

Tailed (directional)

hypothesis!


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Experimental designs: Independent groups, repeated

measures and matched pairs.

In a basic experiment there are two conditions the experimental condition andthe control condition. A decision has to be taken as to whether a participant will

take part in both conditions or whether they will only participate in one. The

decision taken will determine the experimental design. At AS you are expected

to know the following experimental designs:

A) Repeated Measures Design

B) Independent groups design

C) Matched pairs design

A) Repeated measures design:

In a repeated measures design every participant will take part in both conditions of

the independent variable, in effect each participant acts as their own control. Thus if

we were investigating the effect of organisation on memory, the participant would

take part in both the organised and the unorganised condition.

B) Independent groups design:

In an independent group design the participants take part in either the

control or the experimental condition.

C) Matched pairs Design:

In this design each participant in one of the experimental conditions is matched as

closely as possible with a participant in the other condition. Examples of variablesthat they could be matched on include age, gender, intelligence and personality traits.

When the matching pairs have been established they are randomly allocated to one or

other of the conditions.

SEE table below for advantages and disadvantages of the

different experimental designs as well as when each should be

used.

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Pgs 106-108


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Design Description When should it

be used?

Advantages Disadvantages Controls

Repeated

measures

design.

The same

participants are

used in bothconditions

When there is only

a small number of

participants- thesame participants

can be used for

both conditions.

Participant variables

are eliminated.

Uses fewer

participants: it is

sometimes difficult

to get people to

participate in

research.

Identifying

participants can be

time consuming.

Order effects

can occur eg-

fatigue, learningor boredom.

Increased

chance of

demand

characteristics

occurring

Cannot use the

same stimulus

materials.

Order effects

can be

counter-balanced.

Demand

characteristics

can be reduced

using single

blind

techniques.

Independe

nt groups

design

Participants are

randomly allocated

to either one or

other of the

conditions

When you have lots of

participants. This

design is not affected

as much by the

number of

participants, although

in a small sample

theres a risk that any

differences between

conditions could be

due to individual

differences.

No order effects.

Reduced chance of

demand

characteristics.

Can use the same

stimulus materials.

Least effective

design for

controlling

participant

variables

More

participants

required

Absolutely

essential that

participants

are randomly

allocated to

the different

conditions.

Matched

pairs

design

Participants are

matched as closely

as possible with

another

participant and

then the pairs are

randomly allocated

to either one or

the other

conditions.

When you have a lot

of time, money and

participants as they

need to be carefully

matched.

No order effects

Good attempt at

controlling

participant variables.

Difficult to

match

participants

exactly

More

participants

required.

Identical twins

provide

researchers

with a very

close match

for participant

variables.

Order Effects: An effect that can occur when a repeated measures design is employed. If the participants always complete one

condition first, by the time they get to the second condition they may experience order effects, such as practice, boredom and fatigue.

This could then affect their performance in the second condition.

Counterbalancing: The method used to balance order effects in the repeated measures design. Half the participants would complete the

experiment in one sequence- for example condition A first followed by condition B. The other half would do condition B first followedby condition A- the easy way to remember is ABBA.


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How are Naturalistic observations designed?

Naturalistic Observations:

These are observations where the researcher observes naturally occurring

behaviours. This type of observation cannot be used in a true experiment where

the researcher manipulates the independent variable to observe the effect on the

dependent variable. However, naturalistic observations can be used in quasi-

experiments such as natural experiments.

A key design issue with naturalistic observational studies is deciding

how to sample the behaviour to be studied. The possibilities include:

i) Time interval sampling: Observing and recording whathappens in a series of fixed time intervals (eg: every 10

minutes or other suitable time interval).

ii) Time point sampling: Observing and recording the

behaviour which occurs at a series of given points in time

(eg: Meal Times).

iii) Event sampling: Observing and recording a complete

event, such as a teacher encouraging a pupil.

Further consideration also needs to be given to behavioural categories, that is,

the way in which data are organised and recorded. Possible methods include

preparing notes, producing a checklist or tally chart, or using a rating scale.

BELOW: AN EXAMPLE OF COLLECTION OF DATA CONCERNING AN

OBSERVATION OF AGGRESSIVE BEHAVIOUR IN CHILDREN.

Child Hits or

shovesunprovoked

Hits or

shovesfollowing

peers

Hits or

shoves inretaliation

Shouts at

othersunprovoked

Shouts at

othersfollowing

peers

Shouts at

others inretaliation.

A III II I II

B I III III

C IIII I I

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Pgs 112-113


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Operationalisation of the dependent and independent

variable.

What are variables?A variable is simply the precise, technical term that

psychologists use for something. These can include a quality,

such as attractiveness, a characteristic such as weight or height

or an action such as behaviour. Variables can change or vary.

What are dependent and independent variables?The dependent variable (DV) is the variable that is affected by changes in

the independent variable (IV).

The independent variable (IV) is the variable that the researcher

manipulates and which is assumed to have a direct effect on the dependent

variable (DV).

EXAMPLE: If you study for your exams you are likely to get good results.

Therefore, studying time would be the IV here and results the DV as your

grades are likely to be influenced by amount of time spend studying.

NOTE: IT IS VERY IMPORTANT TO UNDERSTAND THAT AN

INDEPENDENT VARIABLE AND A DEPENDENT VARIABLE ARE ONLY USED

IN AN EXPERIMENTAL HYPOTHESIS.

How do we operationalise variables?

Operationalising is the process of devising a way of measuring a

variable. What this means is that the exact nature and method of

measuring or observing the variables must be defined. When thevariables have been defined clearly and objectively, the

researcher is said to have produced operational definitions. This is

needed in order to test the hypothesis.

If for example the hypothesis stated that:

Participants who read digits out loud will later recall greater number of

digits than participants who read the digits sub-vocally.

In the above example, you could operationalise memory through thenumber of digits recalled, otherwise how else would memory be measured?

- 20 -

Pg 95-96

Pg 91


21/38

In addition, the researcher would need to define clearly what reading out-

loud means and what sub-vocally means. The researcher would also need to

identify how they intend to observe and measure the incidence of each of

these variables in the investigation, when all this has been done, the

hypothesis is testable!

What is a pilot study?

A pilot study is a trial of the experiment. During

the pilot study the researcher needs to test the

reliability of the data collection tool and make

any necessary changes before carrying out the

full investigation. The researcher would also testthe validity of the data to be collected.

What are extraneous (confounding) variables and how

can we control them?

Extraneous variables (EVs) is the term for any variables other than theI.V that might affect the DV. Where EVs are important enough to provide

alternative explanations for the effects, they become confounding

variables.

Evs need to be controlled to ensure that any effect on the DV is a direct

manipulation of the IV, if confounding variables are not controlled then the

study will lack in internal validity.

There are a number of different types of confounding variables that need

to be taken into account when designing or investigating research, these

include the following:

A) Situational variables: these refer to variables related to the

research situation eg: Temperature, instructions, time of day and

lighting, materials used in the investigation are all situational

variables. Situational variables are controlled through

standardisation; that is that the only thing that differs between

the two conditions is the IV.

- 21 -

Pg 106

Pg 96


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B) Participant variables: These refer to variables that are connected

with the research participants eg: intelligence, age, gender and

personality. Participant variables can be controlled through the

research design such as match pairs design where participants in

one condition are matched with participants of similarcharacteristics in the second condition eg: someone of similar age,

intelligence etc.

What is meant by reliability and validity?

Reliability means that two or more measurements or observations of

the same psychological event will be consistent with each other. For

example, imagine two researchers are observing the same person at

the same time in the same situation and are rating the

persons behaviour using an observation checklist.

There must be a high level of consistency between

the two sets of observations. The key word to

emphasise when talking about reliability is

consistency i.e. the same or similar results are obtained with

different measuring tools or every time a study is replicated.

Validity means that we are actually measuring what we claim to be

measuring. There are two broad categories of validity; Internal

validity and external validity.

Internal validity: a research study has high internal validity if the

outcome of the study is the result of the variables that are

manipulated in the study (all confounding variables must be

controlled).

External validity: The extent to which the

findings can be generalised to the wider

population and to different situations.

This relates to population validity- do thefindings apply to different groups of people?

This can also relate to ecological validity- do the

findings apply in different settings (ie- does the

study approximate to real life situations?).

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Pg 92


23/38

Below are three ways of measuring validity:

Method of assessingvalidity

Explanation

Face validity This method involves a quick eyeball test, that is doesit looks like the study/ instrument/ experiment is

measuring what it claims to be measuring?

Concurrent validity This involves comparing the results from the new testwith one from an older test known to have reliability eg:

if a participant scored 148 on an old well established IQ

test but only 113 in a new IQ test, then questions would

be raised about the validity of the new test.

Predictive validity This is the ability of the test to predict performance infuture tests. If it can do this then it is said to have good

predictive validity eg: are GCSEs good predictors of A-

Level grades?

Ethical guidelines and Ethical issues in research:

Why do we need ethical guidelines?

Ethics in the conduct of research is extremely important. Researchcan directly or indirectly cause psychological, cultural or physical

harm to a person, a community or a culture if it disregards the best

interests of those who participate. To avoid hostility between

possible participants and researchers, the BPS code of ethics

highlights nine different ethical guidelines which should help to

protect participants.

- 23 -

TIP: When asked to evaluate a new study, always consider the sample used- does it have high or low

population validity? What kind of design does it use, does the study have high ecological validity?

Also consider the internal validity of the study by thinking about possible demand characteristics/

investigator effects and confounding variables as these can all impact on the results of the study and

thus reduce internal validity. You might also want to consider the reliability of the study.

Pg 92

Pg 100-102


24/38

British Psychological Society (BPS) Code of Ethics:1) Consent: Participants need to be provided with the aims of the research

study and of anything that might influence their willingness toparticipate in a study before they can give their fully informed

consent to participate. In addition, children under the age of 16 or

anyone with mental or learning difficulties would need to obtain

consent from a parent/ guardian prior to participating in research.

2) Deception: Information must not be withheld from participants, nor should

they be misled, if they are likely to object when debriefed at the end of

the procedure. Alternative to deception should always be considered.

3) Debriefing: following an investigation, participants should be fully informed

about the nature of the research. The participants experiences of the

research should be discussed. Debriefing following an investigation does

not justify the use of unethical procedures.4) Withdrawal from investigation: participants have the right to withdraw at

any time, regardless of whether or not they were paid for their

participation. They are allowed to withdraw at any point during the study

and in this case the researcher would need to destroy any data collected

on the participant.

5) Confidentiality: participants have the right to

confidentiality. If confidentiality cannot be

assured, then this must be disclosed to participants

before they consent to participate. The Data

Protection Act requires you to maintain the

confidentiality of those people about whom you

have collected information.

6) Protection of participants: psychologists have a

responsibility for protecting their participants

from physical or mental harm, including undue

stress. The risk of harm to participants must not exceed that of their

every-day life.

7) Observational research: observational studies must protect the privacy

and psychological well-being of those observed. Where consent for

observation has not been obtained, privacy is an important issue.

Participants should not be observed in situations where they would notexpect others to observe their behaviour.

8) Giving advice: psychologists are not allowed to give advice to their

participants unless they are fully qualified to do so, instead they must re-

direct participants to a more appropriate source.

9) Colleagues: where you feel a colleague might be following an unethical

procedure, you are under the obligation of raising the concern with the

colleague and encourage them to re-evaluate their study.

- 24 -

TIP: There is a difference between an ethical issue and ethical guidelines. The guidelines

tell the researcher what to do and the ethical issue occurs when there is a conflict betweenwhat the researcher wants to do for the research and the rights of the participants.


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PTO for how to deal with Ethical issues

Ethical Issues and ways in which psychologists deal with them:

Ethical issue Why is it an ethical issue? Methods for dealing with ethical issues

Deception Deception is an ethical issue because it

prevents that participant from giving

informed consent and they may find

themselves in research against their wishes.

It is also an issue because the participants

may start to become distrustful of

psychologists in the future, which can createproblems for future researchers.

Debriefing: informing the participant of

true aims of the study after the study has b

conducted, this is to restore the participant

the state they were in prior to the resea

taking place.

Retrospective informed consent/ right

withdraw form the study: once the tnature of the experiment is revealed,

participants have a right to withdraw their d

from the study.

Informed

Consent

Lack of informed consent means that

participant has not agreed to take part in the

study, this can also apply to volunteers who

might have not been fully informed about the

aims of the study, it is an ethical issue

because it breaks ethical guidelines and

because it could also lead to distrust of

researchers.

Prior general consent: This involves obtain

the participants consent to be involved i

research study involving deception. O

obtained, it can be safely assumed that t

would apply to future studies too.

Presumptive consent: asking a random sample

the population whether they would consentparticipate in a study involving deception;

they consent then it can be assumed t

participants would also consent.

Children: the consent of the childs paren

guardians or those in loco parentis such

teachers could give consent on their behalf.

Protection of

participants

Participants have the right to not be harmed

as a result of participating in research

studies. The participant should always leave

an experiment in the same psychological and

physical state in which they first began it. If

they are harmed they could suffer long-term

damage that might impact on their future

lives.

The researcher should remind participants t

they can withdraw at any point during the st

should they become overly stressed.

The researcher should terminate any resea

where participants may be suffering more t

originally anticipated.

Debriefing is an important aspect of ensur

protection of participants.

Milgrams study violated all of the above ethical guidelines!

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Selecting your participants for the research study

How does a researcher choose his/her

participants?The first step is deciding who your target population will be. It is

important that the sample is representative of the entire

population so that the findings can be generalised to the rest of

the population. Sampling is a key consideration when considering

the validity of the study, in particular, population validity.

The three sampling techniques are Random, Opportunity and

Volunteer sampling.

Definition Method Population validity

Random A sample in which every member

of the target population has an

equal chance of being selected.

Every member of the target

population is identified and a

random sampling technique is

employed to select the

sample.

EG: names drawn from a hat

High in population val

because it is

representative sampl

the entire t

population.

Opportunity A sample that consists of those

people who are available to the

researcher.

The researcher would

approach people and ask them

to take part in the research.

The researcher takes

advantage of whoever

happens to be available and is

willing to participate.

EG: A teacher gives her

students a questionnaire to

complete and then uses this

as her sample.

High chance that

sample will be bi

leading to low popul

validity.

Volunteer A sample where the participants

self-select. That is they

volunteer to take part in the

research.

The researcher would

advertise their research and

the people who respond would

be the sample.

Research has found t

particular type of pe

is likely to volunteer

research; thus this

of sampling has a

chance of bias, leadin

low population validity.

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Pg 98-99


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What are Demand characteristics?

Demand characteristics are cues in the environment that help the

participant work out what the research hypothesis is. This can lead to

social desirability effects, where the participant behaves in a way that the

hypothesis will be supported or the screw you effect where the

participant will purposefully disrupt the research.

Demand characteristics could lead to low internal validity as often people

change their behaviour to conform to what they think are theexperimenters expectations, these are fuelled by cues in the environment

and can have a negative impact on the study by affecting the results of the

study and as a consequence, lead to low internal

validity.

Demand characteristics can be controlled by using

a single-blind technique, this is when the researcher

knows the hypothesis but the participants do not.

What are investigator effects?

Investigator effects relates to the influence of the researcher whereby

their expectations of what the research outcome should be could lead to a

self-fulfilling prophecy. The researcher may at an unconscious level behave

in such a way as to bring about their own prediction. Investigator effects

relate to the aspects of the investigators appearance or behaviour that

could also lead participants to act in a particular way.

Investigator effects can also lead to low internal validity as it can mean

that participants are not behaving naturally, this in turn impacts on the

results of the study leading to low internal validity.

Investigator effects can be controlled by using a double-blind

technique; this is when the researcher gets an assistant to act on their

behalf. The assistant does not know the hypothesis of the study and

neither do the participants

- 27 -

TIP: When considering the validity of a study think hard about the sample used, is the sample

representative of the entire target population? Was a random method used? By answering these questions

you can assess the external validity (population validity) of a study.Pg 96-97


28/38

SECTION 3:Data analysis and presentation:


Understanding data:In research there are two types of data that a researcher can

collect, these are qualitative and quantitative data. The type of data

collected will have an impact on how you present and analyse your

findings. Quantitative data refers to numerical data, whereas

qualitative data refers to data obtained from unstructured

interviews/ observations etc.

Type of data Advantages Disadvantages

Quantitative Allows for a broader study, involving a greater numberof participants, and therefore increasing population

validity and generalisation of results.

Can allow for greater objectivity and accuracy of

results, less subject to investigator bias and

interpretation.

The research can be replicated, and then analysed andcompared with similar studies. Quantitative methods

Results are limited as they provide numerical

descriptions rather than detailed narrative and

generally provide less elaborate accounts of hu

behaviour or ideas.

The research is often carried out in an unnatura

artificial environment, meaning that studies oft

lack ecological validity.

Preset answers will not necessarily reflect how

- 28 -

Research Methods: (iii) Data analysis and presentation: candidates

should be familiar with the following features of data analysis,

presentation and interpretation:

Presentation and interpretation of quantitative data including

graphs, scattergrams and tables. Analysis and interpretation of quantitative data. Measures of

central tendency including median, mean, mode. Measures of

dispersion including ranges and standard deviation.

Analysis and interpretation of correlational data. Positive and

Negative correlations and the interpretation of correlation

coefficients (Included in section 1)

Presentation of qualitative data

Processes involved in content analysis.


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allow us to summarise vast sources of information and

facilitate comparisons across categories and over time.

people really feel about a subject and in some

cases might just be the closest match.

Qualitative Provides depth and detail : looks deeper thananalysing ranks and counts by recording attitudes,feelings and behaviours .

Creates openness: encouraging people to expand on

their responses can open up new topic areas not

initially considered

Simulates people's individual experiences: a detailed

picture can be built up about why people act in certain

ways and their feelings about these actions

Attempts to avoid pre-judgements: if used alongsidequantitative data collection, it can explain why a

particular response was given

Usually fewer people studied: collection ofqualitative data is generally more time consumin

that quantitative data collection and therefore

unless time and budget allows it is generally

necessary to include a smaller sample size, mean

that validity is compromised.

Less easy to generalise: because fewer people

are generally studied it is not possible to

generalise results to that of the population

(Population validity).

Difficult to make comparisons: for example, ifpeople give widely differing responses that are

highly subjective.

Open to investigator effects: due to the close

interaction between researchers and participant

there is a greater chance of investigator effect

occurring, these would compromise the validity o

the data obtained.

What are data tables:

When data is collected as a result of research it is important for the

researcher to present their findings in an accessible form. This allows

patterns to be seen clearly; an easy way of doing this is to present your

findings in a table:

Measure of central

tendency

Condition 1

(organised condition)

Condition 2

(unorganised

condition)

Mean 7.8 6.2

Median 9 7.0

Mode 10 7.0

In the above table, it is clear that the numbers are referring to the

number of words recalled and the finding that more words are recalled

when information is organised is clearly visible.

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Pg 123- 124


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What are m easures of central tendency:

There are three measures of central tendency, the mean, the median and

the mode. Identifying the central tendency in a set of data tells a

researcher where the average is in a set of data.

Measure of

Central

Tendency

What is it? Advantages Disadvantages

Mean * The mean is the statistical or

arithmetic average.* It can be calculated by adding up all

the scores in a set of data and then

dividing by the number of scores.

The mean is the most

sensitive measure of centraltendency, taking all scores

into consideration.

The mean can be dis

by extreme scores wiconsequence that

becomes unreprese

of the data.

Median * This is the middle score after the

data is organised according to size.

* The median is calculated by first

putting the data in order and then finding

the middle score. If there is an even

number of scores you should add the two

in the middle and then divide by two.

The median is unaffected by

extreme scores, thus in a

data where extreme scores

exist this would be a more

appropriate measure of

central tendency than the

mean.

Unlike the mean, the

only takes one or two

into accountthe

value(s)

Mode * This is the most frequently occurring

score.

* It can be calculated by a frequency

countquite simply analyse your data and

see which score occurs the most.

Similar to the median, the

mode is unaffected by

extreme scores.

Can be ef

dramatically by the

in one score, making

unrepresentative mea

When should we use each of the different measures of

central tendency?

Generally the arithmetic mean will give a good indication of central

tendency or the typical mean score unless the data contains

extreme scores that distort it.

Should there be extreme scores then the mean can be

misleading and shouldnt be used. The median, in contrast,

wont be affected by extreme scores and can easily be located

as the middle item in a data set.

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However, the median may still not tell us what the typical or most frequent

scores in a set of data. If we want to know this, the mode would be the

best measure of central tendency to use.

What are measures of dispersion?

Measures of dispersion describe the spread of the data, or its

variation around a central value (i.e. How spread out are the

data?). The two measures of dispersion that we look at in AS are

Standard Deviation and the Range.

RANGE: the range is simply the difference between the highest

and the lowest score and is calculated by subtracting the lowest

score from the highest score.

STANDARD DEVIATION: The SD measures how widely spread the values

in a data set are around the mean. The standard deviation allows us to see

the consistency with which the IV impacted on the DV.

Standard Deviation What this tells us about the data:

Large A large standard deviation tells us that there was much variationaround the mean.

Small A small standard deviation tells us that the data was closely

clustered around the mean.

Zero All the data values were the same!

The advantages and disadvantages of the different measures of

Central Dispersion are summarised below:

Measure of

dispersion

What is it? When should it be used? Advantages Disadvantages

Range The differencebetween the

highest and the

lowest score in a

set of data.

When you wish to make a

basic measure of the

variation within the data and

the data is consistent. If

there are extreme scores the

range is inappropriate as it

will be a distorted measure

of variation.

Easy to calculate The range can b

easily distorted b

extreme scores.

- 31 -

TIP: A common exam question is to ask you to identify and justify an alternative measure of central tendency to the one given inthe stimulus material. For example, if the measure used in the stimulus material is the arithmetic mean an alternative would be themedian or the mode. The most common mistake is to explain what it is rather than to say why you would use this instead. EG: I

would use the median as an alternative to the mean as there are some extreme scores in the data which would distort the mean,making it unrepresentative. The median would have the advantage that it is unaffected by these extreme scores, making it a more

suitable measure of central tendency.

Pg 126-127


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Standard

Deviation

A measure of

dispersion that

indicates the

spread or

dispersion of the

data around acentral value.

When you wish to make a

very sensitive measure of

dispersion.

Takes account

of all scores.

It is a sensitive

measure of

dispersion

Harder t

calculate than th

range.

Graphs:

Statistics such as those discussed previously provide one way of describing

and representing patterns in a quantitative data set. Another way, is

through the use of statistical graphs. These have the advantage of

providing a visual representation of the data set that allows us to

see the patterns in a data set in an easy to understand way.

Histograms:

A histogram is often used in data analysis to provide a visual

illustration of the distribution of data items in a data set. A

histogram consists of vertical bars of equal width, which represent

the frequencies of the variable placed on the X axis. The major

features of the Histogram can be summarised as follows:

1) All categories are represented.2) Columns are of equal width per equal category

3) No intervals are missed because they are empty

4) Column areas are proportional to the area represented.

Bar Charts:

Bar charts like line charts, are useful for comparing classes or

groups of data. A bar chart can represent frequencies or single

statistics such as the mean of a sample or the percentage ofproportion. There is no need to show all the frequencies on the

X-axis, only the ones you are interested in displaying.

Scattergram:

A scattergram gives a good visual picture of the relationship between the

two variables and aids the interpretation of the correlation coefficient.

Each piece of data contributes to one point on the scattergram, on which

points are plotted but not joined. The resulting pattern indicates the type

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Pg 129-130


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and strength of the relationship. Points to consider about a scattergram

are:

1) The more the points tend to cluster around a straight line, the

stronger the relationship between the two variables (the strongerthe correlation).

2) If the line around which the points tends to cluster runs from lower

left to upper right, the relationship between the two variables is

positive.

3) If the line around which the points tends to cluster runs from upper

left to lower right, the relationship between the two variables is

negative.

SEE PAGE 5 FOR EXAMPLES OF SCATTERGRAMS AND POSITIVE

AND NEGATIVE CORRELATIONS.

Qualitative data and analysis

Qualitative analysis involves the analysis of non-numerical data. This

can include speech, books, magazines, videos, television, pictures and

computer games, as well as reflections and accounts of personal

experience. If participants complete an interview or questionnaire using

open ended questions then it will produce some qualitative data.

Content analysis:Content analysis is the way in which qualitative data is sometimes

converted into quantitative data to make interpretation easier to

understand. Depending on your research, you can decide what elements

of the answers you are going to count before you see any data to

prevent your own ideas influencing how you code the data. In any case,

appropriate categories would have to be identified.

Below is an example from imagined accounts of a bank robbery,

participants were asked to imagine a bank robbery, here are the

answers from some of the participants:

1) I imagine a crowded room with lots of people in queues in front of

the cashiers. Then I imagine two men bursting in wearing balaclavas

and brandishing guns. The whole thing is over very

quickly, they tell the customers to lie on the floor

and keep still; they force the cashiers to hand over

bags of money and they run out as you hear the

police sirens in the distance.

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Pg 131-132


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2) I think of three or four men with masks on running into a bank with

guns, shouting at everybody to get down on the ground. Lots of

scared bystanders. They get into the vault, fill up a bag with money

and then make a quick exit in their car.

3) I imagine men dressed in stripy shirts with black trousers and black

eye masks and black beanie style hats and black gloves. I imagine

that there are three of them and that they rush through the door

with hand-held pistols and force the cashier to give them money at

gun point. There are people screaming in the background and sirens

begin to wail, they stuff money into bags and run out into a black

Cadillac car.

4) Guns, Swag bags, masks, murky CCTV footage, shouting, fear,

running, speeding getaway car, creaming tyres. TV news item.

5) People queuing, masked men, wearing black running in and shouting

everyone get down on the floor waving guns. Someone going to the

cashiers with a briefcase and demanding they fill it with the cash

and open the safe. Then all running out and someone behind the cash

desks pressing the alarm.

Looking through the answers, the following categories are formed and

whenever someone mentions one of these is it counted:

1) The bank robbers are male- IIII

2) The bank robbers wear some kind of disguise- IIII + I

3) The bank robbers wear dark clothes- II

4) The bank robbers demand money from the cashiers- IIII

5) The bank robbers have a getaway car waiting outside the bank- II

6) The getaway car has a driver in it- 0

VALIDITY:

One of the main problems with using content analysis is that of validity. It

is vital that the classification procedure is reliable in the sense of being

consistent. Also, the practice of constructing a category system involves

the risk of an investigator imposing his or her meaning-system on the data

content, rather than taking it from the content. In content analysis

studies, it is often desirable for multiple coders (investigators) to set

about the task of negotiating categories and quantifying the featurespresent within a given text.

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Pure qualitative analysis:

This approach rejects the conversion of qualitative data to quantitative

data like above, instead it aims to present the findings of the research in a

purely verbal form. Analysis attempts to organise the data not by reducing

them to a number but by identifying and categorising recurrent themes.

The process of achieving this level of analysis involves:

1) The data collected being transcribed (EG write out theanswers given in an interview in the exact form in which

the interviewee gave them).

2) Once transcribed the data would be read through

repeatedly in an effort to identify recurrent themes.

3) All data is read and re-read until all emerging themes

have been identified that account for all data collected.

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GLOSSARY:

KEY TERM: Definition:

Hypothesis A precise testable statement about the expected outcome of a

investigation.

Aim A general statement about the purpose of the investigation.

Experiment A research investigation in which one specific variable is manipulated t

observe its effects, if any, on another specific variable, while keeping a

other variables controlled. In a true experiment, participants are randomlallocated to conditions or take part in all conditions.

Variable A measurable characteristic or value that can differ from one perso

to another or have multiple values.

Experimental

Hypothesis

A hypothesis used in the context of an experiment.

Alternative

Hypothesis

Any hypothesis other than the null hypothesis.

Correlational

study

An investigation into the possible association of two variables.

Operationalising The process of devising a way of measuring a variable.

Internal Validity A research study or experiment has internal validity when the outcome o

the study is the result of the variables that are manipulated in the study.

External

validity

The extent to which findings can be generalised to settings other tha

the research setting. This includes population validity, which is th

question of whether the findings can be generalised to other peopl

and ecological validity, which is the question of whether the result

can be generalised to other settings.

Independent

Variable (IV)

The variable that the researcher manipulates and which is assumed t

have a direct effect on the dependent variable.Dependent

Variable (DV)

The variable that is affected by changes in the independent variable.

Extraneous/

Confounding

variables

This is a general term for any variables other than the IV that might hav

an effect on the DV.

Ethical issues These occur when there is a dilemma between what the researche

wants to do in order to conduct the research and the rights an

dignity of the participants.

Control group This is the group of participants who do not receive the experimenttreatment or condition so that they can act as a comparison to th

- 36 -


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participants who do.

Laboratory

experiment

An experiment that is carried out in a controlled environment wher

the independent variable is manipulated.

Mundane Realism The extent to which a study matches the real-world situation to which i

will be applied.Field

Experiment

An experiment that takes place in a natural environment: th

independent variable is manipulated.

Natural

Experiment

The researcher takes advantage of a naturally occurring variable. Not

true experiment as variations in the IV can occur naturally rather tha

through being manipulated by the researcher.

Ecological

Validity

The extent to which the methods, materials and setting of th

experiment approximates the real-life situation being studied.

Experimental

design

The method of control imposed by the experimenter to control fo

participant variables. This is one of the major methods employed in a

experiment to control Extraneous Variables.Order effects A confounding effect that can occur when a repeated measures desig

is employed. If the participants always complete one condition first

by the time they get to the second condition they may experienc

order effects, such as practice, boredom and fatigue. This could the

affect their performance in the second condition.

Counterbalancing The method used to balance order effects in the repeated measure

design. Half the participants would complete the experiment in on

sequence- for example condition A followed by condition B. the other hal

would do condition B first followed by condition A. The easy way t

remember this is ABBA.

Observer Bias This happens when an observer makes their own particula

interpretation of the behaviour they observe.

Participant

observation

Requires the researcher to actually join the group or take part in th

situation they are studying.

Non-Participant

Observation

Based on observations made from a distance or from outside the grou

or situation being studied.

Disclosed

observation

An observation in which the participants are aware that they are bein

observed. Sometimes known as overt observations.

Undisclosedobservations

An observation in which the participants are not aware that they arbeing observed. This is also known as covert observation.

Structured

observation

Before the research begins the researcher determines precisely wha

behaviours are to be observed and will use a standardised checklist t

record the frequency with which those behaviours are observed within

specified time period.

Unstructured

observation

The researcher uses direct observation to record behaviours as the

occur; there is no predetermined plan about what will be observed.

Observational

schedule

Usually a structured form or grid that is completed in line with th

researchers instructions or guidance by an observer.

Inter-observer The extent to which a data collection tool used by a group o

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reliability observers produces similar data.

Social

desiribility

The tendency of humans to present themselves in the best possible ligh

Responses to questionnaires may be influenced by this tendency. There i

a difference between what people say they do and what in fact they do!

Idiographic Relating to individual cases or events.Qualitative data Analysis that focuses more on words (what people say) rather tha

numbers.

Quantitative

data

Analysis that uses numerical data.

Coding The procedure employed to transform raw data into a format that can b

used for data analysis purposes. This is necessary to allow the conversio

of qualitative data to quantitative data. Coding qualitative data involve

identifying recurrent words, concepts or themes.

Quasi

experiment

An experiment that takes place in a field setting but the independen

variable is already set, ie: is not controlled by the investigator.

Research Methods Booklet -TES Version

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