Research Methods Booklet -TES Version

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, psychologis psychologists ts differ from “lay people” in that they develop develop scientific theories, which they then test by carrying out carefu carefully lly design designed ed resear research ch studie studies. s. The main main method methodss used by psychologists to carry out their research include expe experi rime ment nts, s, corr correl elat atio ionn tech techni niqu ques es,, obse observ rvat atio iona nall tech techni niqu ques es,, case case stud studie iess and and self self-r -rep epor ortt tech techni niqu ques es including including interviews interviews and questionna questionnaires. ires. Psychologi Psychologists sts use research methods to gather and make sense of the data they produce.

SECTION 1:

Research Methods and Techniques: Area of Specification Being Covered: 

Research Methods: (i) Methods and Techniques, candidates will be expected to demonstrate knowledge and understanding of the following research methods, including their advantages and weaknesses: Experimental method, including laboratory, field and natural experiments. 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 everything else you study in psychology. When you are evaluating a theory you should look to the evidence that supports the theory—use your knowledge of research methods to judge the credibility of the evidence offered. This will significantly enhance your use of analytic and evaluative skills.

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Research Methods and Techniques: Pgs 106-107

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: Manipulationn of the independent independent variable: variable: the independen independentt variable variable 1. Manipulatio (IV) is directly manipulated to produce a change in the dependent variable (DV). 2. Randomisation:

a true true expe experi rim ment ent requ requir ires es tha that participant participantss are randomly allocated allocated to conditions conditions or that the the part partic icip ipan ants ts take take part part in each each cond condit itio ionn of the 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 treat treatme ment nt or cond conditi ition on so that that they they can can act act as a comp compar aris ison on to the the participants who do.

What are the different types of experiments?  e xperiments?   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 th e independent variable. Control of all other extraneous variables. Participants are randomly allocated to conditions.

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Research Methods and Techniques: Pgs 106-107

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: Manipulationn of the independent independent variable: variable: the independen independentt variable variable 1. Manipulatio (IV) is directly manipulated to produce a change in the dependent variable (DV). 2. Randomisation:

a true true expe experi rim ment ent requ requir ires es tha that participant participantss are randomly allocated allocated to conditions conditions or that the the part partic icip ipan ants ts take take part part in each each cond condit itio ionn of the 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 treat treatme ment nt or cond conditi ition on so that that they they can can act act as a comp compar aris ison on to the the participants who do.

What are the different types of experiments?  e xperiments?   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 th e independent variable. Control of all other extraneous variables. Participants are randomly allocated to conditions.

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(ii) Advantages and disadvantages of Lab experiments: 

Advantages: •

•

High High leve levels ls of cont contro rol, l, both both the the IV and and Evs Evs are are cont contro roll lled ed,, 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 mean that that it coul could d easi easily ly be appl applie ied d to diffe differe rent nt grou groups ps of people people particu particular larly ly to other other culture cultures/ s/ setting settingss increa increase se 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 They lack lack munda mundane ne real realis ism m (sit (situa uati tion onss are are very very artif artifici icial al), ), ther theref efor ore e resu result ltss cann cannot ot alwa always ys be gene genera rali lise sed d to othe otherr situations.

An example of a lab experiment is Ainsworth’s strange situation. B)

Field Experiment:

A field field expe experim rimen entt is an expe experim rimen entt that that take takess plac place e in a natu natura rall environment. The typical features of field experiments include: a. Direct Direct manipu manipulat lation ion of the indepe independe ndent nt variab variable. le. Partic icip ipan ants ts are are not not nece necess ssar aril ilyy rand random omly ly b. Part 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. Reduce Reduced d demand demand charac character terist istics ics,, which which means means that intern internal al 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. 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 would need 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:

Pgs 116- 117

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 covariables. 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 the number 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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(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 the strength 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 or practical reasons (e.g. the relationship between time spent in day care 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.

For example, in the relationship between stress and illness, it may not be that stress causes illness but instead that people under stress have less healthy lifestyles and it is this which i n turn causes the illness. -6-

Disadvantages continued… •

Correlations only identify linear relationships not curvilinear. 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

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 observations—this 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 of observation 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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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 “Ainsworth’s strange situation (1970)”, where children were studied under laboratory conditions where she could control all other variables and observed 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, nonparticipant 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 unaware that 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 standardised checklist 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 disadvantages:

methods

has

advantages

and

A major problem faced by observational studies is observer bias. This happens when 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 Advantages observation High levels of ecological validity. Naturalistic

Controlled

Participant

Nonparticipant

Disclosed observation

Undisclosed observation

Participants may be unaware that they are being observed and therefore they may behave more naturally. Higher levels of control over E.V’s

Very high ecological validity

Disadvantages No control over E.V’s If the participant is unaware that they are observed, then this may raise ethical issue lack of informed consent. Participants may be affected by the fact they are being observed. Behaviour may not be natural; this impacts o ecological validity of the research. The researcher has to rely on memory as cannot take notes (unreliable).

Rich qualitative data can be collected by the research (consider general advantages of this type of Observer may become too emotionally inv data) with the observees, meaning that observ can become subjective rather than objective. Easier to understand what the observees’ behaviour actually means. The presence of the observer may chang group dynamics. A relationship based on trust can be established between those being observed and the observer. Observees may not realise that they are being The actual meaning of the behaviour may n observed meaning that behaviour may not be so clear from a distance. changed by the presence of the observer. A relationship is not formed between The observer may be more objective as they are observer and the observee with the conseq less likely to become emotionally involved with that there may be less trust. the participants. The observer can record their observations as they occur making them more reliable in terms of memory. 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 Reduction of reactivity as the participant does not realise they are being observed, meaning that there are less demand characteristics.

Increase in reactivity as the observee may c their behaviour as they know they are observed. There will be an increase in de 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.

TIP: You may be asked to identify two factors that could affect the validity of an observation. For this focus on confounding variables that could affect the research or observer bias (explain what this is- Observer bias can also reduce the reliability of the data, you would need to suggest ways in which observer bias could be reduced.) You could also focus on the positive aspects, such as naturalistic observations being -9high in ecological validity because t he behaviour is occurring in a natural environment.

Pgs 118-120

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 key considerations 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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What are the advantages and disadvantages of using Questionnaires/ survey methods? Advantages/ strengths: •

•

•

Social desirability: •

The tendency of  humans to present themselves in the  best possible light. There may be a difference in what  people say they do and what they actually do!

•

•

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 isn’t 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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•

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).

Pg 121

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 the question and explain that you would then calculate how many people picked a particular choice (eg: Do you drink  alcohol? Often Sometimes Never).

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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 a case 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: Genie’s 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: - 13 -

Investigation Design: Area of Specification Being Covered: 

Research Methods: (ii) Investigation Design candidates should be familiar with 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 dependent variables. 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. • • •

•

• •

• • • • • •

•

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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Pgs 90- 91

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 the investigation. 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 relationship between the variables being tested. In addition, there is also the “alternative hypothesis” which 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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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 Directional

Non- directional

Null Hypothesis

Definition

Example

A directional hypothesis is more precise than a nondirectional 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 stat more digits will be recalle condition). A non-directional hypothesis is one in which the There will be a difference in t direction of the results is not predicted. This is also of digits recalled in the readi known as a two-tailed hypothesis because the condition compared to the direction of the result is not specified but could go in condition either direction- that is it could be “more or less”. (the direction is not stated hypothesis only states that th a difference but it has not s which condition more or less di recalled). This tends to state that there will be no difference There will be no differenc relationship between the variables being number of digits recalled in t investigated. A null hypothesis is used because it out loud condition compared t makes a very precise prediction (nothing will happen) vocal condition. than can be easily disproved, thereby providing evidence to support the alternative hypothesis.

TIP: When asked to write or to identify a directional hypothesis look out for indicator  words 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 nondirectional hypothesis, so you are saying there will be a difference but you haven’t stated in what direction the difference will be.

Tailed (directional) hypothesis! 

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Experimental designs: Independent groups, repeated Pgs 106-108 measures and matched pairs. In a basic experiment there are two conditions the experimental condition and the 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) B) C)

Repeated Measures Design Independent groups design 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 variables that 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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Design

Description

When should it Advantages be used?

Repeated measures design.

The same When there is only participants are a small number of used in both participantsthe conditions same participants can be used for both conditions.

Disadvantages Controls

Participant variables Order effects are eliminated. can occur egfatigue, learning Uses fewer or boredom. participants: it is sometimes difficult Increased to get people to chance of participate in demand research. characteristics Identifying occurring participants can be time consuming. Cannot use the same stimulus materials. Independe Participants are When you have lots of No order effects. Least effective This nt groups randomly allocated participants. design for design is not affected design to either one or Reduced chance of controlling as much by the other of the demand participant number of conditions characteristics. variables participants, although in a small sample there’s a risk that any differences between conditions could be due to individual differences.

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.

Can use the same More stimulus materials. participants required

No order effects

Difficult match Good attempt at participants controlling exactly participant variables. More participants required.

Order effects can be counterbalanced. Demand characteristics can be reduced using single blind techniques.

Absolutely essential that participants are randomly allocated to the different conditions.

to 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 followed  by condition A- the easy way to remember is ABBA.

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Pgs 112-113

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 quasiexperiments 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)

ii)

iii)

Time interval sampling: Observing and recording what happens in a series of fixed time intervals (eg: every 10 minutes or other suitable time interval). Time point sampling: Observing and recording the behaviour which occurs at a series of given points in time (eg: Meal Times). 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

A

Hits or Hits or Hits or Shouts at shoves shoves shoves in others unprovoked following retaliation unprovoked peers III II I

B

I

III

C

IIII

I

III I

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Shouts at Shouts at others others in following retaliation. peers II

Pg 95-96

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?

Pg 91

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 the variables 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 the number of digits recalled, otherwise how else would memory be measured?

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In addition, the researcher would need to define clearly what reading outloud 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!

Pg 106

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 test the validity of the data to be collected.

What are extraneous (confounding) variables and how can we control them? Extraneous variables (EV’s) is the term for any variables other than the I.V that might affect the DV. Where EV’s are important enough to provide alternative explanations for the effects, they become confounding variables. Ev’s 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.

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Pg 96

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 similar characteristics 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 person’s 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 the findings 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

Pg 92 Below are three ways of measuring validity: Method of validity Face validity

Concurrent validity

Predictive validity

assessing Explanation This method involves a quick “eyeball” test, that is does it looks like the study/ instrument/ experiment is measuring what it claims to be measuring? This involves comparing the results from the new test with 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. This is the ability of the test to predict performance in future tests. If it can do this then it is said to have good predictive validity eg: are GCSE’s good predictors of ALevel grades?

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.

Ethical guidelines and Ethical issues in research:

Why do we need ethical guidelines? Ethics in the conduct of research is extremely important. Research can 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.

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Pg 100-102

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 to participate 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 not expect 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 redirect 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.

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 between what 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.

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.

It is also an issue because the participants may start to become distrustful of psychologists in the future, which can create problems for future researchers.

Informed Consent

Protection participants

Retrospective informed consent/ right withdraw form the study: once the t nature of the experiment is revealed, participants have a right to withdraw their d from the study. Lack of informed consent means that Prior general consent: This involves obtain participant has not agreed to take part in the the participant’s consent to be involved i study, this can also apply to volunteers who research study involving deception. O might have not been fully informed about the obtained, it can be safely assumed that t aims of the study, it is an ethical issue would apply to future studies too. because it breaks ethical guidelines and because it could also lead to distrust of Presumptive consent: asking a random sample researchers. the population whether they would consent participate in a study involving deception; they consent then it can be assumed t participants would also consent.

of 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.

Children: the consent of the child’s paren guardians or those in “loco parentis” such teachers could give consent on their behalf. 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.

Milgram’s study violated all of the above ethical guidelines! 

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Pg 98-99

Selecting your participants for the research study How does a participants?

researcher

choose

his/her

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.

Random

Definition

Method

Population validity

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.

High in population val because it is representative sampl the entire t population.

EG: names drawn from a hat Opportunity

Volunteer

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. A sample where the participants The researcher would self-select. That is they advertise their research and volunteer to take part in the the people who respond would research. be the sample.

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High chance that sample will be bi leading to low popul validity.

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.

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

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 the experimenter’s 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

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SECTION 3:

Data analysis and presentation: Area of Specification Being Covered: 

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. •

•

•

• •

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 number Results are limited as they provide numerical of 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 and compared with similar studies. Quantitative methods

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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

Qualitative

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.

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

Usually fewer people studied: collection of qualitative 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, meani that validity is compromised.

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

Less easy to generalise: because fewer people are generally studied it is not possible to generalise results to that of the population (Population validity).

Attempts to avoid pre-judgements: if used alongside quantitative data collection, it can explain why a particular response was given

Difficult to make comparisons: for example, if people 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.

Pg 123- 124

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 Condition 1 tendency (organised condition) Mean Median Mode

7.8 9 10

Condition 2 (unorganised condition) 6.2 7.0 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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What are measures 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 What is it? Central Tendency 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. 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. Mode * This is the most frequently occurring  score. * It can be calculated by a frequency count—quite simply analyse your data and see which score occurs the most.

Advantages

Disadvantages

The mean is the most The mean can be dis sensitive measure of central by extreme scores wi tendency, taking all scores consequence that into consideration. becomes unreprese of the data. The median is unaffected by Unlike the mean, the extreme scores, thus in a only takes one or two data where extreme scores into account—the exist this would be a more value(s) appropriate measure of central tendency than the mean. Similar to the median, the Can be ef mode is unaffected by dramatically by the extreme scores. 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 shouldn’t be used. The median, in contrast, won’t 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.

Pg 126-127

TIP: A common exam question is to ask you to identify and justify an alternative measure of central tendency to the one given in the stimulus material. For example, if the measure used in the stimulus material is the arithmetic mean an alternative would be the median 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.

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 variation around 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 What is it? When should it be used? Advantages Disadvantages dispersion The difference When you wish to make a Easy to calculate The range can b Range between the highest and the lowest score in a set of data.

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.

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easily distorted b extreme scores.

Standard Deviation

A measure of When you wish to make a dispersion that very sensitive measure of indicates the dispersion. “spread” or dispersion of the data around a central value.

Takes account Harder t of all scores. calculate than th range. It is a sensitive measure of dispersion

Pg 129-130

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 of proportion. There is no need to show all the frequencies on the X-axis, only the one’s 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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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 stronger the 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

Pg 131-132

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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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) 2) 3) 4) 5) 6)

The bank robbers are male- IIII The bank robbers wear some kind of disguise- IIII + I The bank robbers wear dark clothes- II The bank robbers demand money from the cashiers- IIII The bank robbers have a getaway car waiting outside the bank- II 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 features present 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 the answers 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. A general statement about the purpose of the investigation. 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 randoml allocated to conditions or take part in all conditions. A measurable characteristic or value that can differ from one perso to another or have multiple values. A hypothesis used in the context of an experiment.

Aim Experiment

Variable Experimental Hypothesis Alternative Hypothesis Correlational study Operationalising Internal Validity External validity

Independent Variable (IV) Dependent Variable (DV) Extraneous/ Confounding variables Ethical issues

Control group

Any hypothesis other than the null hypothesis. An investigation into the possible association of two variables. The process of devising a way of measuring a variable. 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. 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. The variable that the researcher manipulates and which is assumed t have a direct effect on the dependent variable. The variable that is affected by changes in the independent variable. This is a general term for any variables other than the IV that might hav an effect on the DV. 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. This is the group of participants who do not receive the experiment treatment or condition so that they can act as a comparison to th

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participants who do. Laboratory An experiment that is carried out in a controlled environment wher experiment 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 An experiment that takes place in a natural environment: th Experiment independent variable is manipulated. Natural The researcher takes advantage of a naturally occurring variable. Not Experiment true experiment as variations in the IV can occur naturally rather tha through being manipulated by the researcher. Ecological The extent to which the methods, materials and setting of th Validity experiment approximates the real-life situation being studied. Experimental The method of control imposed by the experimenter to control fo design 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 Requires the researcher to actually join the group or take part in th observation situation they are studying. Non-Participant Based on observations made from a distance or from outside the grou Observation or situation being studied. Disclosed An observation in which the participants are aware that they are bein observation observed. Sometimes known as overt observations. Undisclosed An observation in which the participants are not aware that they ar observations being observed. This is also known as covert observation. Structured Before the research begins the researcher determines precisely wha observation 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 The researcher uses direct observation to record behaviours as the observation occur; there is no predetermined plan about what will be observed. Observational Usually a structured form or grid that is completed in line with th schedule researcher’s 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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