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A Level Psychology > Research Methods > Flashcards

Research Methods Flashcards

Psychology Paper 2

1
Q

what is the aim of a study?

A

what the purpose of a piece of research is.

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2
Q

what is a hypothesis and what are the three types?

A

a prediction of what the results will be and can be directional, non-directional or null.

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3
Q

what is a directional hypothesis?

A

states the direction of the difference or relationship.
- participants will (DV) when (IV1) than (IV2)

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4
Q

what is a non-directional hypothesis?

A

does not state the direction of the difference of relationship.
- there will be a difference in (DV) between (IV1) and (IV2)

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5
Q

what is a null hypothesis?

A

no difference / direction / affect / correlation is stated.
- there will be no difference in (DV) between (IV1) and (IV2)

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6
Q

what is an independent variable (IV)?

A

the cause - the variable that the experimenter manipulates / changes.

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7
Q

what is a dependent variable (DV)?

A

the effect - the variable that the experimenter measures.

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8
Q

what is an extraneous variable (EV)?

A

the variable that is needed to be controlled in an experiment as it could affect the DV.

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9
Q

what is a confounding variable (CV)?

A

any factor that is found after the study has been conducted, which affected the DV but was not controlled for.

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10
Q

what is operationalisation?

A

clearly defining variables in terms of how they can be measured.

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11
Q

what are types of extraneous variables?

A

demand characteristics, investigator effects, participant variables and situational variables.

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12
Q

what are demand characteristics?

A

any cue from the researcher or research situation that might give away the purpose of the investigation and may lead the ppt to change their behaviour (screw-u or please-u effect).

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13
Q

what are investigator effects?

A

any effect of the researcher’s behaviour (conscious or unconscious) on the results of the study (DV) e.g. nodding/smiling, leading questions, design of study, selection of participants.

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14
Q

what are participant variables?

A

any individual differences between participants that might affect the DV e.g. age, intelligence, gender.

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15
Q

what are situational variables?

A

any features of the experimental situation that might affect the DV e.g. noise, time of day, weather.

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16
Q

how are extraneous variables controlled?

A

randomisation and standardisation.

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17
Q

what is randomisation?

A

the use of chance methods to control for the effects of extraneous / confounding variables e.g. bias when designing materials and deciding the order of experimental conditions.

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18
Q

what is standardisation?

A

using exactly the same formalised procedures and instructions for all participants in a research study, this reduces the effect of extraneous/confounding variables.

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19
Q

what is the experimental method?

A

an investigation in which a hypothesis is scientifically tested i.e. an independent variable (the cause) is manipulated and the dependent variable (the effect) is measured; only extraneous variables are controlled.

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20
Q

what are the types of experiment?

A

laboratory, field, natural and quasi.

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21
Q

what is a laboratory experiment?

A

a experiment carried out in a controlled setting, the IV is manipulated to see the impact on the DV whilst the effects of other variables are minimised as far as possible.

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22
Q

what is an example of a laboratory experiment?

A

edit this

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23
Q

what are the strengths of a laboratory experiment?

A
  • extraneous variables are closely controlled, meaning the IV is likely to have affected the DV, increasing the internal validity of the study.
  • research can be easily repeated as there will be a controlled, standardised procedure, increasing the reliability of the results.
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24
Q

what are the weaknesses of a laboratory experiment?

A
  • artificial nature of the set up means that the results may not reflect ‘real-life’ behaviour, so reducing the external/ecological validity of the study.
  • participants know they are being tested so they may change their behaviour (demand characteristics).
  • tasks given in the research may not be reflective of everyday tasks (lack of mundane realism).
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25
Q

what is a field experiment?

A

a controlled experiment conducted outside the laboratory, the IV is still manipulated by the researcher but the experiment takes place in a natural environment.

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26
Q

what is an example of a field experiment?

A

piliavin (1969) got a confederate to collapse in a train when smelling of alcohol or carrying a walking stick and seeing how many people helped in each condition.

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27
Q

what are the strengths of a field experiment?

A
  • there is higher mundane realism than lab experiments, therefore higher external validity.
  • often participants won’t know that they are being studied, so demand characteristics are less of an issue.
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28
Q

what are the weaknesses of a field experiment?

A
  • it is harder to control extraneous variables so harder to know if the IV has affected the DV, lack of internal validity.
  • if participants are unaware they are being studied, this raises ethical issues (lack of informed consent).
  • replication is more difficult as the exact natural situation can not be replicated each time.
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29
Q

what is a natural experiment?

A

an experiment where the IV varies due to a naturally occurring event and the researcher takes the opportunity to study it.

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30
Q

what is an example of a natural experiment?

A

williams (1986) looked at the effects in gender attitudes after the introduction of TV to a small town in canada.

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31
Q

what are the strengths of a natural experiment?

A
  • there is high external validity as the IV is naturally occurring.
  • the effects can be tested of factors that could not be manipulated by the researcher e.g. the effects of the lack of attachment in romanian orphans.
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32
Q

what are the weaknesses of a natural experiment?

A
  • there is less control over extraneous variables than field experiments.
  • participants can’t be randomly allocated to conditions, introducing the possibility of bias.
  • naturally occurring IVs may be rare, so studies can’t be repeated.
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33
Q

what is a quasi experiment?

A

an experiment where the IV cannot be manipulated by the researcher so they use a naturally occurring IV.

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34
Q

what is an example of a quasi experiment?

A

gender differences in attitudes towards food.

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35
Q

what are the strengths of a quasi experiment?

A

it can be tested under controlled conditions, increasing the scientific credibility of the research and allows replication.

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36
Q

what are the weaknesses of a quasi experiment?

A
  • participants can’t be randomly allocated to conditions, introducing possible confounding variables.
  • it is difficult to control for extraneous variables so it is difficult to establish cause and effect.
  • researchers cannot be certain that the IV caused the DV.
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37
Q

what is an experimental design?

A

it refers to the way in which participants are used in experiments (how they are arranged).

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38
Q

what are the 3 experimental designs?

A

independent groups, repeated measures and matched pairs.

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39
Q

what is the independent groups design?

A

participants are allocated to different groups where each group represents one experimental condition (each participant only does one condition).

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40
Q

what are the strengths of the independent groups design?

A
  • no issue of order effects.
  • less time consuming
  • less chance of demand characteristics
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41
Q

what are the weaknesses of the independent groups design?

A
  • it is difficult and expensive, different participants need to be recruited for each condition.
  • participant variables may be an issue, results may be due to a confounding variable rather than manipulation of the IV which can reduce the validity of findings.
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42
Q

how can participant variables be controlled for in the independent groups design?

A

random allocation

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43
Q

what is random allocation?

A

an attempt to control for participant variables which ensures that each participant has the same chance of being in one condition as any other (by distributing participants into each condition through the use of random techniques).

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44
Q

what is the repeated measures design?

A

all participants take part in all the conditions of the experiment, (each participant takes part in both conditions).

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45
Q

what are the strengths of the repeated measures design?

A
  • no participant variables - participants take part in both conditions so there is more confidence that results were due to the manipulation of the IV, meaning there is higher validity.
  • it is time efficient and cost effective, the same participants are used twice (at least) so extra participants do not need to be recruited.
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46
Q

what are the weaknesses of the repeated measures design?

A
  • order effects, repeating two tasks could create boredom or fatigue which could deteriorate the participants’ behaviour in the second condition or performance may improve due to knowledge of first task, therefore order acts as a confounding variable.
  • an increased chance of demand characteristics, it is more likely that participants will work out the aim of the study when experiencing all conditions of the experiment.
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47
Q

how can order effects be controlled for in the repeated measures design?

A

counterbalancing

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48
Q

what is counterbalancing?

A

an attempt to control for the effects of order, in counterbalancing half the participants experience the conditions in one order (condition A then B) and the other half in the opposite order (condition B then A).

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49
Q

what is the matched pairs design?

A

pairs of participants are matched on some variable(s) that may affect the DV, then one member of the pair is assigned to condition A and then the other to condition B.

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50
Q

what are the strengths of the matched pairs design?

A
  • participants only take part in one condition so order effects and demand characteristics are less of a problem.
  • reduced risk of participant variables, due to matching process so findings are more valid.
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51
Q

what are the weaknesses of the matched pairs design?

A
  • difficult and expensive, different participants need to be recruited for each condition.
  • can be time-consuming due to pre-test process.
  • difficult to match participants identically, matching is a more complex process.
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52
Q

what does the term population refer to?

A

a group of people who are the focus of the researcher’s interest, from which a smaller sample is drawn.

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53
Q

what is a sample?

A

a group of people who take part in a research investigation, the sample is drawn from a (target) population and is presumed to be representative of that population.

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54
Q

what are sampling techniques?

A

the method used to select people from the population.

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55
Q

what are the 5 sampling techniques?

A

random, volunteer, opportunity, systematic and stratified

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56
Q

what is random sampling?

A

each member of the target population has an equal chance of being selected through chance methods e.g. picking names out of a hat.

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57
Q

what are the strengths of random sampling?

A

there is internal validity, lack of extraneous / confounding variables due to the sample being potentially unbiased.

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58
Q

what are the weaknesses of random sampling?

A
  • difficult and time-consuming, a complete list of the target population may be extremely difficult to obtain.
  • selected participants may refuse to take part.
  • it is possible that the sample may end up being unrepresentative rather than representative.
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59
Q

what is volunteer sampling?

A

participants put themselves forwards to take part in a study.

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60
Q

what are the strengths of volunteer sampling?

A

it is easy, convenient and less time-consuming due to the participants being more engaged than others so there is less of an effort needed from researchers.

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61
Q

what are the weaknesses of volunteer sampling?

A

volunteer bias - only a certain type of people will be attracted so representativeness is reduced.

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62
Q

what is systematic sampling?

A

when every nth member of the target population is selected and a sampling frame is produced, which is a list of people in the target population organised in a way.

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63
Q

what are the strengths of systematic sampling?

A

the method is objective, the researcher has no influence after selection so it is likely to be representative.

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64
Q

what are the weaknesses of systematic sampling?

A

it is time-consuming and participants may refuse to take part, resulting in a volunteer sample.

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65
Q

what is stratified sampling?

A

the sample reflects the proportions of people in certain sub-groups (strata) within the target population, to carry out a stratified sample the researcher first identifies the different strata that make up the population and then the proportions needed for the sample to be representative are worked out.

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66
Q

what are the strengths of stratified sampling?

A

the sample is representative because it is designed to accurately reflect the composition of the population so the findings are more generalisable.

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67
Q

what are the weaknesses of stratified sampling?

A

it is hard to represent differences in people so complete representation of the target population is not possible.

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68
Q

what is opportunity sampling?

A

a technique where the participants are available at the time of the study.

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69
Q

what are the strengths of opportunity sampling?

A

it is convenient, much less time consuming and costly than other methods.

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70
Q

what are the weaknesses of opportunity sampling?

A
  • there is a high chance of obtaining an unrepresentative sample.
  • the researcher has complete control over the selection of participants, could lead to researcher bias.
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71
Q

what are ethical issues?

A

they arise when a conflict exists between the rights of participants in research studies and the goals of research to produce authentic, valid and worthwhile data.

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72
Q

what is informed consent?

A

it involves making participants aware of the aims of the research, the procedures, their rights (including to withdraw) and what their data will be used for, from the researcher’s point of view, asking for informed consent may make the study meaningless because the participants’ behaviour will not be ‘natural’.

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73
Q

what is deception?

A

deliberately misleading or withholding information from participants at any stage of the investigation, there can be occasions where deception can be justified if it does not cause the participant distress.

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74
Q

what is protection from harm?

A

participants should not be placed at any more risk than they would be ‘normally’ and they should be protected from physical and psychological harm.

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75
Q

what is privacy?

A

participants have the right to control information about themselves, if this is invaded the confidentiality should be protected, this right to privacy extends to where the study takes place (institutional / geographical location not named).

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76
Q

what is confidentiality?

A

it refers to our right to have any personal data protected.

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77
Q

what is the british psychological society (BPS) code of conduct?

A

it is a set of ethical guidelines that researchers have a duty to observe when conducting research.

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78
Q

how to deal with informed consent?

A

participants should be issued with a consent letter or form detailing all relevant information that might affect their decision to participate.

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79
Q

how to deal with deception and protection from harm?

A

at the end of the study participants should be given a full debrief (where participants are made aware of the true aims and any extra details), they should also be told what their data will be used for and given the right to withdraw / withhold data, participants may also require counselling, which the researcher should provide, if they experience any embarrassment or stress.

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80
Q

how to deal with confidentiality?

A

personal details must be protected (maintain anonymity), researchers usually refer to participants by number or initials and during briefing/debriefing participants are reminded that their data will be protected.

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81
Q

what is a pilot study?

A

a small-scale version of an investigation that takes place before the real investigation is conducted, the aim is to ensure that there are no issues and if necessary the researcher is able to make changes/modification.

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82
Q

what is a single-blind procedure?

A

participants are not aware of the aims/conditions until the end of the study to control for the confounding effects of demand characteristics.

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83
Q

what is a double-blind procedure?

A

neither participants nor individual conducting research know the aim/condition of the study.

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84
Q

what are observational techniques?

A

involve observing actual behaviours which are subsequently recorded.

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85
Q

what are the types of observation?

A

naturalistic, controlled, covert, overt, participant and non-participant.

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86
Q

what is a naturalistic observation?

A

it is conducted in the environment where the behaviour would normally occur e.g. in a classroom.

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87
Q

what are the strengths of a naturalistic observation?

A

it is high in external validity as there are more natural behaviours and findings can be generalised to real life.

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88
Q

what are the weaknesses of a naturalistic observation?

A

it can be difficult to replicate so cannot check reliability, as researcher is not in control of variables.

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89
Q

what is a controlled observation?

A

it often takes place in a laboratory setting where researchers control some variables e.g. bandura’s study.

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90
Q

what are the strengths of a controlled observation?

A

replication is much easier as confounding/extraneous variables are less of a factor, reliability can be checked.

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91
Q

what are the weaknesses of a controlled observation?

A

there is low ecological validity due to the researcher recording behaviours in artificial environments.

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92
Q

what is a covert observation?

A

participants are unaware that they are the focus of the study and their behaviour is observed in secret (covertly).

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93
Q

what are the strengths of a covert observation?

A

investigator effects are unlikely meaning that participants’ behaviour will be genuine, leading to an increase in internal validity.

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94
Q

what are the weaknesses of a covert observation?

A

it is less ethical as participants are not aware that they are taking part and cannot give consent.

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95
Q

what is an overt observation?

A

when participants know that their behaviour is being observed and have given their informed consent beforehand.

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96
Q

what are the strengths of an overt observation?

A

it is possible to inform participants in advance and obtain informed consent.

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97
Q

what are the weaknesses of an overt observation?

A

behaviour can be distorted through investigator effects in which the participants change their behaviour through social desirability bias.

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98
Q

what is a participant observation?

A

when the observer becomes part of the group they are studying.

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99
Q

what are the strengths of a participant observation?

A

the researcher can gain a greater insight into the experiences of those being observed (gives rich qualitative data) which increases external validity and high ecological validity (true to real life).

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100
Q

what are the weaknesses of a participant observation?

A
  • the researcher may lose objectivity as they become part of the study and can be unethical due to ethical issues (deception).
  • it can be dangerous and time-consuming and collecting data can be difficult.
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101
Q

what is a non-participant observation?

A

the researcher remains separate from those they are studying and records behaviour in a more objective manner.

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102
Q

what are the strengths of a non-participant observation?

A

the researcher is more likely to remain objective so there is less danger of them adopting characteristics of the ‘lifestyle’ they are observing, higher in validity (investigator effects less likely).

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103
Q

what are the weaknesses of a non-participant observation?

A

the researcher may lack the extra insight gained from being a participant themselves, as they are removed/far from the environment they are studying.

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104
Q

what is a structured observation?

A

an observation study using predetermined coding scheme to record the participants’ behaviour.

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105
Q

what are the strengths of a structured observation?

A
  • data is much easier to analyse to spot trends and make conclusions.
  • data is more likely to be numerical, therefore quantitative, so more straightforward.
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106
Q

what are the weaknesses of a structured observation?

A

data is in less detail as only certain things have been recorded.

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107
Q

what is an unstructured observation?

A

observation where there is no checklist so every behaviour seen is written down in as much detail as possible.

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108
Q

what are the strengths of an unstructured observation?

A

qualitative data is produced so more detail.

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109
Q

what are the weaknesses of an unstructured observation?

A
  • qualitative data is much more difficult to record and analyse.
  • there is more risk of observer bias (only recording things that fit with the observer’s preconceived ideas) and only may record ‘appealing’ behaviours.
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110
Q

when designing observations, what things do researchers need to decide?

A
  • which type of observation?
  • unstructured or structured?
  • behavioural categories (structured)?
  • which sampling method to use? (time/event)
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111
Q

what are behavioural categories?

A

when designing a structured observation, psychologists must decide which specific behaviours should be examined - key behaviours or collections of behaviours, that the researcher conducting the observation will pay attention to and record.

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112
Q

what are the strengths of behavioural categories?

A

makes data collection more structured and objective and to be useful, categories should be unambiguous and clear (categories should also be exclusive and not overlap).

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113
Q

what are the weaknesses of behavioural categories?

A

it can be difficult to ensure that the categories do not overlap because some behaviours may be too similar to be able to tell the difference e.g. ‘grinning’ and ‘smiling’.

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114
Q

what are the 2 sampling methods?

A

time sampling and event sampling.

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115
Q

what is time sampling?

A

a researcher records behaviours within prescribed intervals e.g. every 5 minutes.

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116
Q

what are the strengths of time sampling?

A

effective in reducing the number of observations that have to be made.

117
Q

what are the weaknesses of time sampling?

A

behaviour recorded may be less representative of the whole observation.

118
Q

what is event sampling?

A

the researcher records every time a behaviour (event) occurs e.g. counting and recording every time aggressive behaviour is seen.

119
Q

what are the strengths of event sampling?

A

useful when the target behaviour or event happens infrequently.

120
Q

what are the weaknesses of event sampling?

A

other important behaviours may be missed.

121
Q

what are the 4 ways in which observers can ensure inter-observer reliability?

A
  • observers should familiarise themselves with the behavioural categories to be used.
  • they then observe the same behaviour at the same time.
  • observers should compare the data they have recorded and discuss any differences in interpretations.
  • finally observers should analyse the data from the study, inter-observer reliability is caused by correlating each pair or observations made and an overall figure is produced.
122
Q

what is a self-report technique?

A

any method in which a person is asked to state or explain their own feelings, opinions, behaviours and/or experiences related to a given topic.

123
Q

what are 2 self-report techniques?

A

questionnaires and interviews.

124
Q

what is a questionnaire?

A

a set of written questions (or ‘items’) used to assess a person’s thoughts and/or experiences - may be used as part of an experiment to assess the DV.

125
Q

what is an open question?

A

it is a question that does not have a fixed range of answers and respondents are free to answer in any way, tends to produce qualitative data.

126
Q

what is a closed question?

A

it is a question that offers a fixed number of responses, can produce both quantitative or qualitative data depending and qualitative data can turn into quantitative data e.g. the number of yes/no responses.

127
Q

what are the strengths of questionnaires?

A
  • cost-effective.
  • can gather large amounts of data quickly because they can be distributed to large numbers of people.
  • can be completed without the researcher being present which reduces effort and time.
  • data produced is usually straightforward to analyse and comparisons can be made.
128
Q

what are the weaknesses of questionnaires?

A
  • the responses given may not always be truthful, respondents may present themselves in a positive light which influences their answers (a form of demand characteristics - social desirability bias).
  • may often produce a response bias, where respondents tend to reply in a similar way throughout e.g. always ticking ‘yes’, which may be because they complete the questionnaire too quickly and fail to read questions properly.
129
Q

what is an interview?

A

a ‘live’ encounter (face-to-face or on the phone) where the interviewer asks a set of questions to assess an interviewee’s thoughts and/or experiences.

130
Q

what is a structured interview?

A

made up of pre-determined set of questions that are asked in a fixed order.

131
Q

what are the strengths of structured interviews?

A

they are straightforward to replicate due to their standardised format, the format also reduces differences between interviewers.

132
Q

what are the weaknesses of structured interviews?

A

it is not possible for interviewers to deviate from the topic or explain their questions as this will limit the richness of the data collected as well as limit unexpected information.

133
Q

what is an unstructured interview?

A

there are no set questions, there is a general aim that a central topic will be discussed and interaction tends to be free-flowing - the interviewee is encouraged to expand and elaborate their answers.

134
Q

what is a semi-structured interview?

A

there is a list of questions that have been worked out in advance but interviewers are also free to ask follow-up questions based on previous answers.

135
Q

what are the strengths of unstructured interviews?

A

there is more flexibility, the interviewer is more likely to gain insight into the thoughts/experiences of the interviewee, including eliciting unexpected information.
- (counterpoint): however this may lead to increased risk of interviewer bias.

136
Q

what are the weaknesses of unstructured interviews?

A
  • analysis of data is not straightforward, irrelevant information and drawing firm conclusions may be difficult.
  • there is a risk that interviewees may lie for reasons of social desirability.
137
Q
A
138
Q
A
139
Q
A
140
Q

what is correlational analysis?

A

a method of analysis which allows a researcher to investigate the relationship between two variables, called co-variables.

141
Q

what are correlations illustrated by?

A

scatter graphs

142
Q

what are the types of correlation?

A

positive, negative and zero/no.

143
Q

what is a positive correlation?

A

as one co-variable increases so does the other.

144
Q

what is a negative correlation?

A

as one co-variable increases, the other decreases.

145
Q

what is zero/no correlation?

A

when there is no relationship between the co-variables.

146
Q

what is a correlation co-efficient?

A

a number between +1 and -1 that tells how closely the co-variables in a correlation are related, the nearer to 1, the stronger the correlation.

147
Q

what is the difference between a correlation and an experiment?

A

correlations show a relationship between variables while an experiment shows cause and effect.

148
Q

what are the strengths of correlational analysis?

A
  • useful tool for research, assessing strength and direction of a relationship can provide a precise and quantifiable measure of how 2 variables are related, which may suggest ideas for future research.
  • often used as a starting point for research to assess possible patterns between variables.
  • quick and cheap to carry out, no need for a controlled environment and manipulation of variables, data collected by others can be used so less time-consuming.
149
Q

what are the weaknesses of correlational analysis?

A
  • demonstrating a cause-effect link is not possible and researchers don’t know if co-variables can cause the other to change and why (establishing direction of effect is an issue).
  • another untested variable may be causing the relationships between the 2 co-variables - an intervening variable (third variable problem).
  • findings of correlational studies are often reported as facts, leading to misinterpretations which could have consequences.
150
Q

what are the 4 types of data?

A

primary, secondary, quantitative and qualitative.

151
Q

what is primary data?

A

original data or first hand data that has been collected specifically for the research being carried out.
- data which is gathered by conducting an experiment, questionnaire, interview or observartion.

152
Q

what are the strengths of primary data?

A

it targets relevant information and it is authentic data obtained.

153
Q

what are the weaknesses of primary data?

A

it requires time and effort and possibly money (resources)

154
Q

what is secondary data?

A

data that has already been collected by somebody else and so pre-dates the current research project.
- data may be located on websites, in articles etc.

155
Q

what are the strengths of secondary data?

A

may be inexpensive and easily accessed requiring minimal effort.

156
Q

what are the weaknesses of secondary data?

A

data may be outdated or not meet study’s standards so may challenge validity of any conclusions.

157
Q

what is quantitative data?

A

numerical data, open to being analysed statistically and can be easily converted into graphs, charts etc.

158
Q

what are the strengths of quantitative data?

A
  • simple to analyse so comparisons are easily drawn.
  • data is more objective and less open to bias.
159
Q

what are the weaknesses of quantitative data?

A

much narrower in meaning and less detail than qualitative so lacks validity.

160
Q

what is qualitative data?

A

written data, often acquired from interviews or unstructured observations.

161
Q

what are the strengths of qualitative data?

A

much more detail offered, so tends to have greater external validity.

162
Q

what are the weaknesses of qualitative data?

A
  • often difficult to analyse.
  • conclusions often rely on subjective interpretations and may be subject to bias.
163
Q

what is a meta-analysis?

A

‘research about research’ - refers to the process of combining results from numerous studies on a certain topic to provide an overview.

164
Q

what are the strengths of a meta-analysis?

A

creates large, varied sample so generalisable and there is an increase in validity.

165
Q

what are the weaknesses of a meta-analysis?

A

it is prone to bias as it only represents the same data.

166
Q

what are the measures of central tendency?

A

the general term for any measure of the average value in a data set.

167
Q

what is the mean?

A

the average calculated by adding up all the values in a set of data and dividing by the number of values.

168
Q

what are the strengths of the mean?

A
  • most sensitive as it includes all of the scores/values in the data set.
  • more representative of the data as a whole.
169
Q

what is the weakness of the mean?

A

can be easily distorted by extreme values.

170
Q

what is the mode?

A

the most frequently occurring value in a set of data (bimodal/no mode if all scores are different).

171
Q

what are the strengths of the mode?

A
  • easy to calculate.
  • sometimes the only measure that can be used on certain data e.g. categories.
172
Q

what are the weaknesses of the mode?

A
  • lacks accuracy.
  • not representative of the data overall.
173
Q

what is the median?

A

the middle value in a data set when it is arranged from lowest to highest.

174
Q

what are the strengths of the median?

A
  • extreme values do not affect it.
  • easy to calculate.
175
Q

what is the weakness of the median?

A

less sensitive as not all scores/values are included in the final calculation.

176
Q

what are the measures of dispersion?

A

the general term for any measure of the spread or variation in a set of scores.

177
Q

what is the range?

A

a simple calculation of the spread of scores, which is worked out by subtracting the lowest score from the highest score and adding 1.

178
Q

what is the strength of the range?

A

easy to calculate.

179
Q

what is the weakness of the range?

A

only takes account of 2 most extreme values which may be unrepresentative of the data set as a whole.

180
Q

what is standard deviation?

A

a measure of spread in a set of scores, it is a single value which tells us how far scores deviate from the mean, the larger the SD scores, the greater the spread.

181
Q

what is the strength of standard deviation?

A

a much more precise measures of dispersion as it includes all values within the final calculation.

182
Q

what is the weakness of standard deviation?

A

all values included can be distorted by a single extreme value.

183
Q

how can quantitative data be presented and displayed?

A

graphs, tables, scattergrams, bar charts and histograms.

184
Q

what is a bar chart?

A

a type of graph in which the frequency of each variable is represented by the height of the bars.

185
Q

when are bar charts used?

A

data is divided into categories (discrete data).

186
Q

what are scattergrams?

A

a type of graph that represents the strength and direction of the relationship between co-variables in a correlational analysis.

187
Q

what is a histogram?

A

a type of graph which shows frequency but, unlike a bar chart, the area of the bars represents frequency, the x-axis must start at a true zero and the scale is continuous.

188
Q

what is a normal distribution?

A

a symmetrical spread of frequency data that forms a bell-shaped pattern, the mean, median and mode are all located at the highest peak (so all have the same midpoint of the curve).

189
Q

what is a skewed distribution?

A

a spread of frequency data that is not symmetrical, where the data clusters to one end.

190
Q

what is a positive skew?

A

a type of frequency distribution where most of the distribution is concentrated towards the left of the graph and the long tail is on the positive (right) side of the peak.
- the mode is at the highest point, then the median and the mean is towards the ‘tail’ - pulled right.

191
Q

what is a negative skew?

A

a type of frequency distribution where most of the distribution is concentrated towards the right of the graph and the long tail is on the negative (left) side of the peak.
- the mode is at the highest point, then the median and the mean is towards the ‘tail’ - pulled left.

192
Q

what is a peer review?

A

the assessment of scientific work by others who are specialists in the same field, to ensure that any research intended for publication is of high quality.

193
Q

what are the 3 main aims of peer review?

A
  • to allocate research funding.
  • to validate the quality and relevance of research.
  • to suggest amendments or improvements.
194
Q
A
195
Q

what are the strengths of peer review?

A
  • validity and accuracy of research is established.
  • anonymity is likely to produce a more honest appraisal.
196
Q

what are the weaknesses of peer review?

A
  • anonymity may be used as a way of criticising rival researchers.
  • researchers prefer to publish positive results which means research that does not mean the criteria is ignored or disregarded, so this creates a false impression of the current state of psychology.
  • reviewers tend to be critical of research that contradicts their own view and more favourable to one that matches it - maintaining their status quo.
197
Q

what is the economy?

A

the state of a country or region in terms of the production and consumption of goods and services.

198
Q

how can psychological theories be applied by governments and companies to improve how the economy functions?

A
  • a psychologically healthy and well-educated population can be more productive, producing more and higher quality goods and services.
  • the consumption of goods and services depends on a population able an willing to buy those goods and services, a psychological understanding and manipulation of desire (e.g. effective and advertising) increase demand.
  • generation of tax revenue that pays for public services depends on taxing income, which depends on people employed in producing and consuming goods and being convinced to pay their taxes.
199
Q

what are examples of psychological research into attachment that are being used to improve the economy?

A

maternal deprivation: research by harlow (deprivation in monkeys), bowlby (critical period), ainsworth (attachment style) and rutter (romanian orphans) demonstarte intellectual, emotional and physical development can be negatively affected by deprivation early in a child’s life.

200
Q

what is the influence on the economy of these attachment studies?

A

midwives use the psychological knowledge gained about the developmental needs of young children when giving informed advice to expectant mothers, hospitals have improved their policies around family visiting hours for young children and physical contact between mothers and children in the first hours of life, adoption agencies prioritise quick placement of infants in loving families.

201
Q

what do these changes do?

A

they improve the development of children which improves the economy as these adults are likely to be more productive, better adjusted to the demands of adult life and less likely to need costly mental health support as adults.

202
Q

what are examples of psychological research into approaches that are being used to improve the economy?

A

conditioning: behavioural theories of classical (pavlov) and operant (skinner) conditioning explain how to shape and even change human behaviour.

203
Q

what is the influence on the economy of these approaches studies?

A

social media and computer game companies can manipulate their uses to engage with their products more by providing virtual rewards such as ‘likes’, ‘followers’ and ‘levels’, these act as social rewards and result in compulsive use.

204
Q

what do these changes do?

A

they improve the economy as companies can display more adverts, making more money.

205
Q

what are examples of psychological research into drug treatments that are being used to improve the economy?

A

neurotransmitters: the action and imbalance of neurotransmitters are linked to mental health conditions such as anxiety, depression, OCD, schizophrenia etc. and drug therapies can act on neurotransmitters, altering how they function in the brain and reducing symptoms.

206
Q

what is the influence on the economy of these drug treatments?

A

the development of cheap and effective drug treatments has allowed people to reduce symptoms and return to everyday life, including work.

207
Q

what do these changes do?

A

they improve the economy by reducing the cost to the NHS, improving workers’ productivity at work and increasing the number of workers paying taxes.

208
Q

what are case studies?

A

detailed and in-depth investigations of an individual, small group of people, institution or event e.g. people with brain damage, institutional racism, covid-19 pandemic etc.
- often involves ‘unusual’ or rare, one-off events but can also be of typical events e.g. childhood experiences across generations.

209
Q

what kind of data to case studies produce and what kind of studies are they?

A

usually produce qualitative data (e.g. interviews, questionnaires, observations) but can also produce quantitative data (e.g. psychometric testing, brain scans etc.), usually longitudinal.

210
Q

what are the strengths of case studies?

A
  • they create opportunities to gather rich data (i.e. an accurate and exhaustive measure of what the study is hoping to measure), high in validity.
  • studying abnormal psychology can give insight into how something works when it is functioning correctly, such as brain damage and memory (e.g. patient KF).
  • detail collected on a single case may lead to interesting findings that conflict with current theories e.g. localisation of function.
211
Q

what are the weaknesses of case studies?

A
  • there is little control over a number of variables involved in a case study, so it is difficult to confidently establish any causal relationships between variables.
  • case studies are unusual by nature, so replication is unlikely.
  • often use small sample sizes which means the findings cannot be generalised to the wider population.
  • case study’s researcher may become so involved with the study that they exhibit bias in their interpretation and presentation of the data, which lowers the validity.
212
Q

what is content analysis?

A

a type of observational research while involves studying people indirectly via the communications they produce (e.g. spoken interaction, written communication, media), the communication is summarised and described in a systematic way to draw conclusions about behaviour.

213
Q

what is coding?

A

it is the initial stage of content analysis in which it involves categorising information into meaningful units i.e. counting up the number of times a particular word, phrase or event appears in a data set - quantitative data.

214
Q

what is the ‘method’ of coding?

A

data collected -> examining data -> identifying coding units -> analysed by applying coding units -> tally made of amount of times coding unit appears.

215
Q

what is thematic analysis?

A

a form of content analysis that involves identifying themes in the data set (implicit or explicit ideas that are recurrent), these are more descriptive e.g. analysis the way people with mental health issues are portrayed in newspapers, producing themes such as ‘stereotype’, ‘poor treatment’ etc. - qualitative data.

216
Q

what are the strengths of content analysis?

A
  • it is a reliable way to analyse qualitative data as coding units are not open to interpretation and so are applied in the same way over time and with different researchers.
  • easy technique to use and not too time consuming.
  • allows a statistical analysis to be conducted if required as there is usually quantitative data as a result of the procedure.
  • deals with ethical issues as material is usually widely available and accessible.
217
Q

what are the weaknesses of content analysis?

A
  • causality cannot be established as it merely describes the data.
  • as it only describes the data it cannot extract any deeper meaning or explanation for the data patterns arising.
218
Q

what is reliability?

A

a measure of consistency (stays the same).
- psychological investigations are said to be reliable if the results are similar each time they are carried out using the same design, procedures and measurements.

219
Q

what are the types of reliability?

A

internal reliability and external reliability.

220
Q

what is internal reliability?

A

it refers to the consistency of a measure within itself e.g. questions in an interview measure the same thing.

221
Q

what is external reliability?

A

it assesses the consistency of a measure from one use to another e.g. reusing asch’s line study to get the same results.

222
Q

what are ways of assessing reliability?

A
  • test-retest
  • inter-rater reliability (or inter-interviewer / inter-observer
  • split-half method
223
Q

what is test-retest reliability?

A

the same test is taken on different occasions and findings are correlated from each test, it shows to what extent the test produces the same/similar answers i.e. if it is consistent or reliable.
- so if the correlation turns out to be significant (and positive) then the reliability is good.
- there also must be significant time between test and retest to ensure that the participant/respondent cannot recall their answers but not so long that their attitudes, opinions or abilities may have changed.

224
Q

what is inter-rater reliability?

A

when different observers use the same measure and their findings are correlated by comparing their data, usually used in a pilot study or at the end of an actual study to make sure behavioural categories are consistently applied.

225
Q

what is the split-half method?

A

data is collected and split randomly in half and compared, to see if results taken from each part of the measure are similar.

226
Q

what are likely reliability issues in questionnaires?

A

produces low test-retest reliability and may require some of the items to be ‘deselected’ or rewritten.

227
Q

how can reliability be improved in questionnaires?

A

by replacing some of the open questions with closed questions as the open questions can lead to misinterpretation, the fixed-choice alternatives may be less ambiguous.

228
Q

what are likely reliability issues in interviews?

A
  • not using the same interviewer each time.
  • asking questions that are too leading.
  • unstructured interviews are less likely to be reliable.
229
Q

how can reliability be improved in interviews?

A

using structured interviews rather than unstructured due to interviewer’s behaviour being more controlled by the fixed questions, so more likely to be reliable.

230
Q

what are likely reliability issues in experiments?

A

unstandardised procedures can cause reliability issues as in order to compare between participants, the procedures must be consistent every time.

231
Q

how can reliability be improved in experiments?

A

reliability can be improved by controlling the conditions of the experiment as far as possible e.g. using standardised instructions, full details of the method being published etc.

232
Q

what are likely reliability issues in observations?

A

categories should not overlap with each other and if they are not operationalised well, different observers have to make their own judgements of what to record where they may end up with differing and inconsistent records.

233
Q

how can reliability be improved in observations?

A

categories need to be fully operationalised and all possible behaviours should be covered to make sure the categories are as objective as possible and less open to individual interpretation, making it more reliable.

234
Q

what is validity?

A

whether a measure actually measures what it claims to be measuring and the extent to which the findings can be generalised beyond the research setting in which they were found.

235
Q

what are the different types of validity?

A

face validity, internal validity and external validity.

236
Q

what is face validity?

A

a measure of wether a tool looks like (subjectively) it measures what it’s supposed to e.g. is an IQ test measuring IQ and not memory.

237
Q

what is internal validity?

A

a measure of whether results obtained are solely affected by changes in the IV in a cause-and-effect relationship - can be assessed based on whether extraneous variables that could also affect results are successfully controlled or eliminated; the greater the control, the better the validity.

238
Q

what is external validity?

A

a measure of whether data can be generalised to other situations outside of the research environment they were originally gathered in.

239
Q

what is a type of internal validity?

A

concurrent validity

240
Q

what is concurrent validity?

A

the extent to which a measure is in agreement with a pre-existing measure that has already been validated, gauged by correlating measures against each other e.g. correlating results on a new depression inventory with beck’s depression inventory.

241
Q

what are the types of external validity?

A

ecological validity and temporal validity.

242
Q

what is ecological validity?

A

how far the findings of a study can be generalised to the real world and other settings e.g. bahrick’s study of LTM.

243
Q

what is temporal validity?

A

whether research findings successfully apply across time (certain variables in the past may no longer be relevant now or in the future) e.g. asch’s line study.

244
Q

what are likely validity issues in questionnaires?

A

participants may answer dishonestly, especially if their results will be ‘open to the public’.

245
Q

how can validity be improved in questionnaires?

A

keeping results anonymous will increase the chances of the participant answering truthfully and having a lie scale built in will also help improve validity.

246
Q

what are likely validity issues in experiments?

A

participant reactivity (when behaviours and reactions are impacted by participants’ knowledge that they are part of a study) and investigator effects (occur when a researcher unintentionally or unconsciously influences the outcome of any research they are conducting), these are extraneous variables.

247
Q

how can validity be improved in experiments?

A

using a control group to compare the results of the experimental group to can improve validity, if the experimental groups results are different to the control group then the IV is likely to have changed the DV and using single and double-blind procedures can reduce the chance of extraneous variables having an impact on an experiment.

248
Q

what are likely validity issues in observations?

A

behavioural categories that are too broad, overlapping or ambiguous may have a negative impact on the validity of the data collected.

249
Q

how can validity be improved in observations?

A

covert observations are likely to be high in validity, as the participant is unaware they are being observed, their behaviour is more likely to be natural and having clear and unambiguous behavioural categories will also improve validity.

250
Q

what are likely validity issues in qualitative methods?

A

the impact that researcher bias has on the answers given and leading questions from the interviewer.

251
Q

how can validity be improved in qualitative methods?

A

depth and detail may increase validity but further enhanced through triangulation.

252
Q

what are the 3 steps that researchers take when choosing a statistical test (the 3 D’s)?

A
  • design: what is the design of the research? - repeated measures, independent groups or matched pairs.
  • difference: is a difference being investigated or a correlation/association?
  • data: is the data nominal, ordinal, interval/ratio? - looking at the DV.
253
Q

what are levels of measurement?

A

this refers to the way in which data are measured, the different levels indicate the strength and gives different types of information about the data collected.

254
Q

what are the 3/4 levels of measurement?

A

nominal, ordinal, interval and ratio.

255
Q

what is nominal level data?

A

the data is represented in the form of categories (sometimes referred to as categorical data), the frequency count of a particular variable is recorded at this level of measurement, these variables are discrete (don’t overlap) and the categories have no natural order - discrete.

256
Q

what is ordinal level data?

A

the data is in a natural order, the numbers represent positions within a group - does not have equal intervals between each unit and also lacks precision due to being based on a subjective opinion.

257
Q

what is interval level data?

A

based on numerical/interval scales that are precise due to having the same distance (equal intervals) between each adjacent point in a standardised scale - continuous data and it is the most precise and sophisticated form of data.

258
Q

what is ratio level data?

A

it is the same as interval level data but with an absolute zero point (but is treated as interval data usually) e.g. time, temperature etc.

259
Q

what do researchers look at when deciding what statistical test to use?

A

the 3 D’s

260
Q

what are the 3 D’s?

A

design, difference and data.

261
Q

what does it mean by design?

A

repeated measures, independent groups, matched pairs?

262
Q

what does it mean by difference?

A

investigating a difference or a correlation/association.

263
Q

what does it mean by data?

A

nominal, ordinal, interval or ratio - looking at the DV.

264
Q

what is a statistical test?

A

used to determine whether the difference found is significant or not, different statistical tests are used for different types of data and studies.

265
Q

when conducting statistical tests what do the null and alternative hypotheses suggest?

A

the null hypothesis suggests no causal relationship exists between the independent variable (IV) and the dependent variable (DV).

the alternative hypothesis suggests a causal relationship.

266
Q

how do researchers decide which hypothesis to accept and which to reject?

A

evidence is collected and the researcher varies levels of the IV and measures the resulting change in the DV, accepting or rejecting either hypothesis depends on whether or not the results of the test match the null or alternative hypothesis.

267
Q

what is the significance of the probability level p=<0.05?

A

psychologists accept a 5% chance that their results are due to chance variation, p=<0.05 means that there is less than a 5% probability the results gained are due to chance.

268
Q

what is the significance of the probability level p=<0.01?

A

occasionally used, this level of significance is usually required of studies attempting to support a controversial theory or if the psychologist is conducting a replication, using this level reduces the probability of accepting the alternate hypothesis in error to less than 1 in 100.

269
Q

how is there always a risk the results of a study are due to chance?

A

due to the random nature of data collection, there is no level or probability we can use that completely removes the possibility of accepting the alternative hypothesis in error.

270
Q

what is a type I error?

A

when researchers accept the alternative hypothesis (reject null) in error, the data collected has passed the level of significance, but really the findings were due to chance variation - using p=<0.05 means this will happen in around 1 in 20 studies.

271
Q

what is a type II error?

A

when researchers reject the alternative hypothesis (accept null) in error, the data has not passed the level of significance, but really the participants not acting as expected is due to chance variation hiding the causal relationship between IV and DV.

272
Q

how can the chance of a type I error be reduced?

A

a researcher can decide to use a p=<0.01 level of significance, however this then increases the likelihood of a type II error.

273
Q

how can the chance of a type II error be reduced?

A

using p=<0.05 level of significance, but increases likelihood of a type I error.

274
Q

how can the statistical tests be remembered?

A

Carrots Should Come Mashed With Swede Under Roast Potatoes
- c = chi-squared
- s = sign test
- c = chi-squared
- m = mann-whitney
- w = wilcoxon
- s = spearman’s rho
- u = unrelated t-test
- r = related t-test
- p = pearson’s r

275
Q

what is the sign test?

A

used to analyse the difference in scores between related items using nominal data.

276
Q

when is a sign test only used?

A

when looking at differences, using a repeated measures design and having nominal data (categories).

277
Q

what is a mann-whitney test?

A

used to determine whether two samples are significantly different.

278
Q

when is a mann-whitney test used?

A

when looking at differences, using an independent groups design (unrelated design) and having ordinal data (ordered).

279
Q

how is a sign test calculated?

A

step 1: subtract each participant’s score in condition B from A, clearly note the sign of each result (+ or -).
step 2: work out the number of participants (N), exclude any participants with the same score in both conditions.
step 3: work out S (the least frequent sign).
step 4: use the critical values table to find the critical value - read across from N calculated and down from the level of significance required.
step 5: compare the critical value to S, if S is equal to or less than the critical value then the results are significant.

280
Q

how is a mann-whitney test calculated?

A

step 1: rank the data for both groups, the lowest number being a rank of 1.
step 2: find the total rank for each group individually.
step 3: for the result to be significant, the calculated value must be equal to or less than the critical value - so the null hypothesis can be rejected and the alternative hypothesis can be accepted.

281
Q

what is a wilcoxon test?

A

used to determine whether two samples are significantly different.

282
Q

when is a wilcoxon test used?

A

when looking at difference, using a repeated measures design (repeated design) and having ordinal data (ordered).

283
Q

how is a wilcoxon test calculated?

A

step 1: calculate the difference between two scores.
step 2: rank the differences (smallest = rank 1 - remove scores with no difference).
step 3: add up the ranks of + difference.
step 4: add up the ranks of - difference.
step 5: work out the value of T - smallest total rank.
step 6: for the result to be significant, the calculated value of T is less than or equal to the critical value of T so the null hypothesis would be rejected and the alternative hypothesis is accepted.

284
Q

what are parametric tests?

A

unrelated t-test, related t-test and pearson’s r.
- more robust and powerful tests and are more likely to detect a significant difference than non-parametric tests.

285
Q

when are parametric tests used?

A
  • the data is interval.
  • the data is normally distributed.
286
Q

what is an unrelated t-test?

A

used to determine whether 2 sets of data are significantly different.

287
Q

when is an unrelated t-test used?

A

when looking at differences, using an independent groups design and having interval level data.

288
Q

how do you calculate the degrees of freedom (df) for the unrelated t-test?

A

Na + Nb - 2

A Level Psychology (11 decks)

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