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Research Methods Flashcards

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1
Q

What are the independent and dependent variables?

A
  • Independent = what you change
  • Dependent = what you measure
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2
Q

What are extraneous and confounding variables?

A
  • Extraneous = nuisance variables that may make it more difficult to detect an effect
  • Confounding = change with the IV, so we cannot be sure if any observed change in the DV is due to the CV or IV
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3
Q

What are demand characteristics?

A

Refers to any cue from the researcher or research situation that may reveal the aim of study, which changes participants’ behaviour

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4
Q

What are investigator effects?

A

Any effect of the investigator’s behaviour on the outcome of the research (the DV) and also on design decisions

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5
Q

What is standardisation?

A

Using exactly the same formalised procedures for all participants in a research study, otherwise differences become EVs

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6
Q

What is a pilot study?

A

A small-scale trial run of an investigation to “road-test” procedures, so that research designs can be modified

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7
Q

What are single blind and double blind procedures?

A
  • Single-blind = a participant doesn’t know the aims of the study so demand characteristics are reduced
  • Double-blind = participant and researcher don’t know the aims of the study to reduce demand characteristics and investigator effects
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8
Q

What is an independent groups design?

A

One group does Condition A and a second group does Condition B. Participants should be randomly allocated to experimental groups

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9
Q

How is no order effects a strength of independent groups?

A
  • Participants are only tested once so can’t practice or become tired
  • This controls CVs
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10
Q

How is participants not guessing aims a strength of independent groups?

A
  • Participants only tested once so are unlikely to guess research aims
  • Therefore, behaviour may be more “natural” (higher realism)
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11
Q

How are individual differences a weakness of independent groups?

A
  • The participants in the two groups are different, acting as EVs/CVs
  • May reduce validity of the study
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12
Q

How are independent groups being less economical a weakness?

A
  • Need twice as many participants as repeated measures for same data
  • More time spent recruiting which is expensive
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13
Q

What is a repeated measures design?

A
  • Same participants take part in all conditions of an an experiment
  • The order of conditions should be counterbalanced to avoid order effects
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14
Q

How is individual differences a strength in repeated measures?

A
  • The person in both conditions has the same characteristics
  • This controls CVs
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15
Q

How is fewer participants a strength of repeated measures?

A
  • Half the number of participants is needed than in independent measures
  • Less time spent recruiting participants
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16
Q

How are order effects a weakness of repeated measures?

A
  • Participants may do better or worse when doing a similar task twice
  • Also, risk of fatigue/practice effects
  • Reduces the validity of the results
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17
Q

How is the participants guessing aims a weakness of repeated measures?

A
  • Participants may change their behaviour (please you/screw you effects)
  • This may reduce the validity of the results
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18
Q

What is a matched pairs design?

A

Two groups of participants are used but they are also matched to each other based on characteristics that matter for the experiment

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19
Q

How are participant variables a strength of matched pairs?

A
  • Participants matched on a variable that is relevant to the experiment
  • This controls participant variables and enhances validity of the results
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20
Q

How is no order effects a strength of matched pairs?

A
  • Participants are only tested once so no practice or fatigue effects
  • This enhances the validity of the results
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21
Q

Matching isn’t always perfect. How is this a weakness of the matched pairs design?

A
  • Matching is time-consuming and can’t control all relevant variables
  • Cannot address all participant variables
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22
Q

How are more participants a weakness of matched pairs?

A
  • Need twice as many participants as repeated measures for same data
  • More time spent recruiting, which is expensive
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23
Q

What is a laboratory experiment?

A
  • Lab experiments are conducted in highly controlled environments
  • This is not always a lab - it could be a classroom, for example, where conditions can be well controlled
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24
Q

How is high control over CVs and EVs a strength of lab experiments?

A
  • Means that the researcher can ensure that any effect on the DV is likely to be the result of manipulation of the IV
  • Thus, we can be more certain about demonstrating cause and effect (high internal validity)
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25
Q

How is replication a strength of lab experiments?

A
  • Possible due to high level of control
  • This ensures new extraneous variables are not introduced when repeating an experiment
  • Replication is vital to check the results of any study to see whether the finding is valid and not just a one-off
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26
Q

Lab experiments may lack generalisability. How is this a weakness of lab experiments?

A
  • Lab environment = artificial and not like everyday life. Participants may behave in unnatural ways due to the unnatural environment, so behaviour cannot always be generalised (low external validity)
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27
Q

How are demand characteristics a weakness of lab experiments?

A
  • Participants are usually aware they’re being tested in a lab experiment (though they may not know why)
  • This may give rise to unusual behaviour, such as demand characteristics
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28
Q

How is low mundane realism a weakness of lab experiments?

A
  • The tasks participants are asked to carry out may not represent everyday experience, e.g. recalling meaningless words
  • This leads to low mundane realism
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29
Q

What is a field experiment?

A
  • In field experiments, the IV is manipulated is a natural, more everyday setting
  • The researcher goes to the participants’ usual environment
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30
Q

How is high mundane realism a strength of field experiments?

A
  • Environment is more natural
  • So field experiments may produce behaviour that is more natural and authentic
  • This is especially the case as participants may be unaware they are being studied (high external validity)
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31
Q

How is loss of control over CVs and EVs a weakness of field experiments?

A
  • A price to pay for increased realism is loss of control of variables
  • This means cause and effect between the IV and DV in field studies may be much more difficult to establish and precise replication is often not possible
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32
Q

How are ethical issues a weakness of field experiments?

A

If participants are unaware they are being studied, they cannot consent to being studied and such research may lead to an invasion of privacy

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33
Q

What is a natural experiment?

A
  • Natural experiments are like a lab or field experiment in that researchers measure effects of an IV on a DV
  • HOWEVER, the researcher has no control over the IV and cannot change it - someone or something else causes the IV to vary, e.g. before and after a natural disaster
  • It’s the IV that is natural, not necessarily the setting. The DV may also be naturally occurring
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34
Q

How is high external validity a strength of natural experiments?

A
  • They involve the study of real-world issues and problems as they happen
  • They also provide opportunities for research that may not otherwise be undertaken for practical or ethical reasons (e.g. Rutter’s Romanian orphans studies)
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35
Q

Participants may not be randomly allocated to experimental conditions (this only applies to independent measures). How is this a weakness of natural experiments?

A
  • This means the researcher might be less sure whether the IV affected the DV. For example, in the study of Romanian orphans, the IV was whether the children were adopted early or late
  • HOWEVER, there were lots of other differences between these groups, e.g. those who were adopted late may have been less sociable than the other children, which may have made them less appealing for potential parents
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36
Q

What is a quasi experiment?

A
  • The IV is based on an existing difference between people (e.g. age or gender). Nobody has manipulated this variable and the IV cannot be changed, unlike in a natural experiment
  • As with a natural experiment, the DV may be naturally occurring (e.g. exam results) or may be devised by the experimenter and measured in the field or a lab
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37
Q

What are the strengths and weaknesses of quasi experiments?

A
  • They’re often carried out under controlled conditions and therefore share some strengths of a lab experiment (e.g. replication)
  • Like natural experiments, quasi experiments cannot randomly allocate participants to conditions, so there may be confounding variables
  • The IV is not deliberately changed by the researcher, so we cannot claim that the IV has caused any observed change
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38
Q

Define population in terms of sampling

A

The largest group of people that a researcher is interested in studying, e.g. college students from the North West

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39
Q

Define sample

A

It’s usually impossible to include all members of the population in the study, so a smaller group is selected (the sample)

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40
Q

Outline generalisation in terms of sampling

A

The sample that is drawn should be representative of the population, so generalisations can be made

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41
Q

Outline bias in terms of sampling

A

Most samples are biased in that certain groups (e.g. men, students etc.) may be overrepresented or underrepresented

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42
Q

Outline the process of random sampling

A
  • Lottery method - all members of the target population are given a number and placed in a hat or computer randomiser is used
  • Every person in the target population has an equal chance of being selected
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43
Q

How is random sampling being potentially unbiased a strength?

A

It means CVs / EVs are controlled, which enhances internal validity

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44
Q

How is random sampling being time consuming a weakness?

A
  • Complete list of the population is hard to get
  • Also, some participants may refuse to participate
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45
Q

Outline the process of systematic sampling

A
  • Participants are selected using a set “pattern” (sampling frame)
  • Every nth person is selected from a list of the target population (e.g. every 3rd person)
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46
Q

How is systematic sampling being unbiased a strength?

A

The first item is usually selected at random, making it an objective method

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47
Q

How is time and effort a weakness of systematic sampling?

A

A complete list of the population is required, which takes time, so may as well use random sampling

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48
Q

Outline the process of stratified sampling

A
  • Sample reflects proportions of people in certain subgroups (strata) within a population
  • Strata are identified, e.g. gender or age groups. The relative percentages of the subgroups in the population are reflected in the sample
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49
Q

How is stratified sampling being a representative method a strength?

A

The characteristics of the target population are represented, so generalisability is more likely than other methods

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50
Q

Stratification is not perfect. How is this a weakness of stratified sampling?

A

Strata cannot reflect all the ways in which people are different, therefore complete representation is not possible

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51
Q

Outline the process of opportunity sampling

A
  • Sample = people who are most available, i.e. the ones who are nearest or easiest to obtain
  • Ask people nearby, e.g. students in your class or people who walk past you in a shopping centre
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52
Q

Opportunity sampling is a quick method. How is this a strength?

A

It’s convenient because you just make use of the people who are closest. This makes it cheaper and one of the most popular sampling methods

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53
Q

How is opportunity sampling being inevitably biased a weakness?

A
  • The sample is unrepresentative of the target population as it is drawn from a very specific area, e.g. one street in one town.
  • This means that the findings can’t be generalised
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54
Q

Outline the process of volunteer sampling

A
  • In a volunteer sample, participants select themselves
  • This is done through advertising, e.g. advert in a newspaper
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55
Q

How is participants being more willing to participate a strength of volunteer sampling?

A

Participants have selected themselves and know how much time and effort is involved, therefore likely to engage more than people stopped in the street

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56
Q

How is volunteer bias a weakness of volunteer sampling?

A

Participants may share certain traits, e.g. want to be helpful, so respond to cues, making generalisations limited

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57
Q

Outline the 4 principles of the BPS code of conduct

A
  • RESPECT - informed consent, confidentiality, deception only to protect the integrity of the research, right to withdraw
  • COMPETENCE - caution in making knowledge claims
  • RESPONSIBILITY - harm and debriefing
  • INTEGRITY - honest and accurate
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58
Q

What is the issue of obtaining informed consent?

A

Allows informed judgement about whether to take part HOWEVER it may reveal the aims of the study

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59
Q

What is presumptive consent?

A
  • Rather than getting consent from the participants themselves, a similar group of people are asked if the study is acceptable
  • If this group agrees, then consent of the original participants is “presumed”
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60
Q

What is prior general consent?

A
  • Participants give their permission to take part in a number of different studies - including one that will involve deception
  • By consenting, participants are effectively consenting to be deceived
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61
Q

What is retrospective consent?

A
  • Participants are asked for their consent (during debriefing) having already taken part in the study
  • They may not have been aware of their participation or they may have been subject to deception
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62
Q

What is the issue of deception?

A

Deliberately misleading or withholding information so consent is not informed HOWEVER, mild deception is okay

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63
Q

What should be done at the end of a study to deal with the issue of deception?

A

Participants should be given a debrief, which should include :

  • The true aims of the investigation
  • Details that weren’t given during the study, e.g. existence of other groups or conditions
  • What their data will be used for
  • Their right to withdraw data
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64
Q

What is the issue of protection from harm?

A

Participants should be at no more risk than they would be in everyday life

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65
Q

What 3 things should be done in order to deal with the issue of protection from harm?

A
  • Participants should be given the right to withdraw at each stage of the research process
  • Should be assured that their behaviour was normal during debriefing
  • Researcher should provide counselling if participants suffered physical or psychological harm
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66
Q

What is the issue of privacy and confidentiality?

A

We have the right to control information about ourselves - if this is invaded, confidentiality should be respected

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67
Q

What 4 things should be done to deal with the issue of privacy and confidentiality?

A
  • If personal details are held, these MUST be protected (a legal requirement)
  • Usually, no personal details are recorded
  • Researchers refer to participants using numbers, initials or false names
  • Participants’ personal data CANNOT be shared with other researchers
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68
Q

Define the floor effect

A

Sometimes the task is too hard, and the researcher may get a floor effect, because none of the participants can score at all / can’t complete the task - ALL PERFORMANCES ARE LOW

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69
Q

Define the ceiling effect

A

When the task is so easy that all participants achieve virtually full marks or top performances and are “hitting the ceiling”

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70
Q

Outline the observational technique

A
  • A way of seeing or listening to what people do without having to ask them
  • Observation is often used within an experiment to assess the DV
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71
Q

The observational technique captures what people do. How is this a strength of the observational technique?

A
  • People often act differently from how they say they will in self-report methods
  • Observations are useful as they give insight into spontaneous behaviour
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72
Q

There is a risk of observer bias with the observational technique. How is this a weakness and how can it be reduced?

A
  • Researcher’s interpretation of the situation may be affected by expectations
  • Bias can be reduced by using more than one observer
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73
Q

Outline the naturalistic technique for observation

A

Takes place where the target behaviour would normally occur

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74
Q

How is high external validity a strength of the naturalistic technique for observation?

A
  • In a natural context, behaviour is likely to be more spontaneous
  • Therefore, it’s more generalisable to everyday life
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75
Q

How is low control of variables a weakness of the naturalistic technique for observation?

A
  • There may be uncontrolled CVs / EVs
  • This makes it more difficult to detect patterns
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76
Q

Outline the controlled technique for observation

A

Some manipulation of variables including control of CVs / EVs

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77
Q

The controlled technique for observation can be replicated. How is this strength?

A
  • More easily replicated due to standardised procedures
  • Findings can be checked to see if they occur again
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78
Q

The controlled technique for observation may have low external validity. How is this a weakness?

A
  • Behaviour may be contrived as a result of the setting
  • Therefore, findings cannot be applied to everyday experience
79
Q

Outline the covert technique for observation

A

Participants are unaware they are being studied

80
Q

Demand characteristics are reduced with the covert technique for observation. How is this a strength?

A
  • Participants do not know they are being watched, so their behaviour will be more natural
  • This increases the internal validity of the findings
81
Q

The covert technique for observation is ethically questionable. How is this a weakness?

A
  • People may not want behaviour recorded, even in public
  • As a result, participants’ right to privacy may be affected
82
Q

Outline the overt technique for observation

A

Participants are aware they are being studied

83
Q

The overt technique for observation more ethically acceptable. How is this a strength?

A
  • Participants have given their consent to be studied
  • They have the right to withdraw if they wish
84
Q

Demand characteristics is an issue with the overt technique for observation. How is this a weakness?

A
  • Knowledge of being studied influences behaviour
  • This reduces the internal validity of the findings
85
Q

Outline the participant observation technique

A

Researcher becomes part of the group they are studying

86
Q

The participant observation technique can lead to greater insight. How is this a strength?

A
  • Researcher experiences the situation as the participants do
  • This enhances the external validity of the findings
87
Q

There is a possible loss of objectivity with the participant observation technique. How is this a weakness?

A
  • The researcher may identify too strongly with those they are studying
  • This is known as “going native”, as was the case wth Zimbardo being the “superintendent” in his Stanford Prison Simulation
88
Q

Outline the non-participant observation technique

A

Researcher remains separate from the group they are studying

89
Q

The non-participant observation technique is more objective. How is this a strength?

A
  • Researcher maintains an objective distance, so less chance of bias
  • May increase the internal validity of the findings
90
Q

There is a loss of insight with the non-participant observation technique. How is this a weakness?

A
  • Researcher may be too far removed from those they are studying
  • May reduce the external validity of the findings
91
Q

Outline the behavioural categories observational design

A
  • The target behaviour to be observed should be broken up into a set of observable categories
  • This is similar to operationalisation
92
Q

It’s difficult to make the behavioural categories design clear and unambiguous. How is this a weakness?

A
  • Categories should not overlap, which is not always possible to achieve
  • “Smiling” and “grinning”
93
Q

There is a possibility for dustbin categories with the behavioural categories design. How is this a weakness?

A
  • All forms of behaviour should be in the list and not one “dustbin”
  • “Dumped” behaviours go unrecorded
94
Q

Outline the event sampling observational design

A

A target behaviour / event is recorded every time it occurs

95
Q

The event sampling design is useful for infrequent behaviour. How is this a strength?

A
  • The researcher will still “pick up” behaviours that do not occur at regular intervals
  • Such behaviours could easily be missed using time sampling
96
Q

Complex behaviours are oversimplified. How is this a weakness of the event sampling design?

A
  • If the event is too complex, important details may go unrecorded
  • This may affect the validity of the findings
97
Q

Outline the time-sampling observational design

A

Observations are made at regular intervals (e.g. once every five minutes)

98
Q

The time sampling observational design reduces the number of observations. How is this a strength?

A
  • Rather than recording everything that is seen (i.e. continuous) data is recorded at certain intervals
  • The observation is more structured and systematic
99
Q

The time sampling observational design may be unrepresentative. How is this a weakness?

A
  • The researcher may miss important details outside of the timescale
  • This may not reflect the whole behaviour
100
Q

Describe closed questions questionnaires

A
  • Respondent has limited choices
  • Data produced tends to be quantitative
  • But it can produce qualitative data
101
Q

Closed question questionnaires can be economical. How is this a strength?

A
  • This means they can provide large amounts of data for relatively low costs
  • Therefore, a large sample size can be obtained which should be representative of the population, which a researcher can then generalise from
102
Q

Closed question questionnaires can provide quantitative data. How is this a strength?

A
  • The respondent provides information which can be easily converted into quantitative data (e.g. count the number of “yes” or “no” answers)
  • This allows statistical analysis of the responses
103
Q

Closed question questionnaires are standardised. How is this a strength?

A
  • All respondents are asked exactly the same questions in the same order
  • This means a questionnaire can be replicated easily to check for reliability
  • Therefore, a second researcher can use the questionnaire to check that the results are consistent
104
Q

Closed question questionnaires lack detail. How is this a weakness?

A

Because the responses are fixed, there is less scope for respondents to supply answers which reflects their true feelings on a topic

105
Q

Outline open questions questionnaires

A
  • Respondent provides own answers expressed in words
  • Data produced tends to be qualitative
106
Q

Qualitative data is obtained from open questions questionnaires

A
  • Rich qualitative data is obtained as open questions allow the respondent to elaborate on their answer
  • This means the researcher can find out why a person holds a certain attitude
107
Q

It’s time consuming to collect the data for open question questionnaires. How is this a weakness?

A
  • It takes longer for the respondent to complete open questions
  • This is a problem as a smaller sample size may be obtained
108
Q

It’s time consuming to analyse the data for open question questionnaires. How is this a weakness?

A
  • It takes longer for the researcher to analyse qualitative data as they have to read the answers and try to put them into categories by coding
  • This is a problem as this is often subjective and difficult
109
Q

Open question questionnaires are not suitable for less educated respondents. How is this a weakness?

A

Open questions require superior writing skills and a better ability to express one’s feelings verbally

110
Q

What is a structured interview?

A

List of pre-determined questions asked in a fixed order

111
Q

Structured interviews are easy to replicate. How is this a strength?

A
  • Straightforward to replicate because of a standardised format
  • The format also reduces differences between interviewers
112
Q

Interviewers cannot elaborate. How is this weakness?

A
  • Interviewers cannot deviate from the topic or explain their questions
  • This may limit the richness of data collected
113
Q

What is an unstructured interview?

A

No set questions, there is a general topic to be discussed, but the interaction is free-flowing and the interviewee is encouraged to elaborate

114
Q

There is greater flexibility with unstructured interviews. How is this a strength?

A
  • Unlike a structured interview, points can be followed up as they arise
  • More likely to gain insight into interviewee’s worldview and collect unexpected interview
115
Q

There is an increased risk of interviewer bias. How is this a weakness of unstructured interviews?

A
  • Closer dialogue between interviewer and interviewee
  • Means more opportunities for unconscious cues
116
Q

What are semi-structured interviews?

A

List of questions that have been worked out in advance, but interviewers ask further questions based on previous answers

117
Q

What 3 things should you avoid when designing questionnaires?

A
  • Avoid jargon
  • Avoid double-barrelled questions
  • Avoid leading questions
118
Q

What is an interview schedule and what can it reduce?

A
  • A standardised list of questions that the interviewer needs to cover
  • It can reduce interviewer bias
119
Q

When designing interviews, what will a quiet room increase?

A

The likelihood that the interviewee will open up

120
Q

When designing interviews, how can you build rapport with the interviewee?

A

Begin with neutral questions to make participants feel relaxed

121
Q

How do you keep the interviews ethical when designing them? (confidentiality)

A

Remind interviewees that answers will be treated in confidence

122
Q

What does a correlation do?

A

Illustrates the strength and direction of an association between two co-variables

123
Q

Describe the layout of a scattergram

A

One co-variable is on the x axis, the other is on the y axis

124
Q

What are the 3 types of correlation and what do the co-variables do in each correlation?

A
  • Positive correlation - co-variables increase together
  • Negative correlation - one co-variable increases, the other decreases
  • Zero correlation - no relationship between variables
125
Q

What is the difference between correlations and experiments?

A
  • In an experiment, the researcher manipulates the IV and records the effect on the DV
  • In a correlation, there is no manipulation of variables and so cause and effect cannot be demonstrated
126
Q

Correlations are a useful starting point for research. How is this a strength?

A
  • By assessing the strength and direction of a relationship, correlations provide a measure of how two variables are reduced
  • If variables are strongly related, it may suggest hypotheses for future research
127
Q

Correlations are relatively economical. How is this a strength?

A
  • Unlike a lab study, there is no need for a controlled environment and can use secondary data (e.g. government statistics)
  • So correlations are less time-consuming than experiments
128
Q

There is no cause and effect with correlations. How is this a weakness?

A
  • Correlations are often presented as causal, e.g. by the media, when they only show how two variables are related
  • This leads to false conclusions about causes of behaviour
129
Q

There are intervening variables with correlations. How is this a weakness?

A
  • Another tested variable may explain the relationship between co-variables
  • This may also lead to false conclusions
130
Q

Define qualitative data

A

Non-numerical data expressed in words, e.g. extract from a diary

131
Q

How is richness of data a strength of qualitative data?

A
  • Much broader in scope than quantitative data
  • More meaningful, greater external validity
132
Q

Qualitative data is difficult to analyse. How is this a weakness?

A
  • Hard to identify patterns and make comparisons
  • Leads to subjective interpretation and researcher bias
133
Q

Define quantitative data

A

Numerical data, e.g. reaction time or number of mistakes

134
Q

Quantitative data is easier to analyse. How is this a strength?

A
  • Can draw graphs and calculate averages
  • So comparisons between groups can be made
135
Q

Quantitative data is narrower in meaning. How is this a weakness?

A
  • Expresses less detail than qualitative data
  • Lower external validity - may be less like “real life”
136
Q

Define primary data

A

“First hand” data collected for the purpose of the investigation

137
Q

Primary data fits the job. How is this a strength?

A
  • Study designed to extract only the data needed
  • Information is directly relevant to research aims
138
Q

Primary data requires time and effect. How is this a weakness?

A
  • Designing and collating questionnaires takes time and expense
  • Secondary data can be accessed within minutes
139
Q

Define secondary data

A

Collected by someone other than the person who is conducting the research, e.g. work of other psychologists or government statistics

140
Q

Secondary data is inexpensive. How is this a strength?

A
  • The desired information may already exist
  • Requires minimal effort, making it inexpensive
141
Q

The quality of secondary data may be poor. How is this a weakness?

A
  • Information may be outdated or incomplete
  • Challenges the validity of any conclusions
142
Q

Define meta-analysis

A
  • A type of secondary data that involves combining data from a large number of studies
  • Calculation of effect size
143
Q

Meta-analyses increase validity of conclusions. How is this a strength?

A
  • The eventual sample size is much larger than individual samples
  • Increases the extent to which generalisations can be made
144
Q

Meta-analyses carry a risk of publication bias. How is this a weakness?

A
  • Researchers may not select all relevant studies, leaving out negative or non-significant results
  • Therefore, conclusions may lack validity
145
Q

Outline the mean as a measure of central tendency

A

Arithmetic average - add up all the scores and divide by the number of scores

146
Q

The mean is a sensitive measure. How is this a strength?

A
  • Includes all the scores / values in a data set within the calculation
  • Represents data set better than median or mode
147
Q

The mean may be unrepresentative. How is this a weakness?

A
  • One very large or small number makes it distorted
  • The median or the mode tend not to be so easily distorted
148
Q

Outline the median as a measure of central tendency

A
  • Middle value, place scores in ascending order and select middle value
  • If there are 2 values in the middle, the mean of these is calculated
149
Q

The median is less affected by extreme scores. How is this a strength?

A
  • The median is only focussed on the middle value
  • In some cases, may be more representative of the data set as a whole
150
Q

The median is less sensitive than the mean. How is this a weakness?

A
  • The actual values of lower and higher numbers are ignored
  • Extreme values may be important
151
Q

Outline the mode as a measure of central tendency

A

Most frequent or common value, used with categorical / nominal data

152
Q

The mode is relevant to categorical data. How is this a strength?

A

When data is “discrete”, i.e. represented in categories, sometimes the mode is the only appropriate measure

153
Q

The mode is an overly simple measure. How is this a weakness?

A
  • The mode may be at one extreme
  • It is not a useful way of describing data when there are many modes
154
Q

Outline the range as a measure of dispersion

A

The difference between highest and lowest value (sometimes 1 is added if values have been rounded up or down)

155
Q

The range is easy to calculate. How is this a strength?

A
  • Arrange values in order and subtract smallest from largest
  • Simple formula, easier than the standard deviation
156
Q

The range does not account for the distribution of scores. How is this a weakness?

A
  • The range does not indicate whether most numbers are closely grouped around the mean or spread out evenly
  • The standard deviation is a much better measure of dispersion in this respect
157
Q

Outline the standard deviation as a measure of dispersion

A
  • Measure of the average spread around the mean
  • The larger the standard deviation, the more spread out the data is
158
Q

Standard deviation is more precise than the range. How is this a strength?

A
  • Includes all values within the calculation
  • Therefore, more accurate picture of the overall distribution of the data set
159
Q

Standard deviation may be misleading. How is this a weakness?

A
  • Can be distorted by extreme values
  • Also, extreme values may not be revealed, unlike with the range
160
Q

Describe tables as a way of presenting quantitative data

A
  • Raw scores displayed in columns and rows
  • A summary paragraph beneath the table explains the findings and draws conclusions
161
Q

Describe bar charts as a way of presenting quantitative data

A
  • Categories (discrete data) are usually placed along the x axis and frequency on the y axis
    • THIS CAN BE REVERSED
  • The height of each column represents the frequency of that item
162
Q

Describe histograms as a way of presenting quantitative data

A
  • Bars touch each other, unlike with a bar chart
  • Data is continuous rather than discrete. There is a true 0
163
Q

Describe scattergrams as a way of presenting quantitative data

A
  • Used for correlational analysis
  • Each dot represents one pair of related data
  • Illustrates strength and direction of correlation
  • The data on both axes must be continuous
164
Q

Describe normal distribution as a way of presenting quantitative data

A
  • Symmetrical, bell shaped curve
  • Most items are in the middle area of the curve with very few at the extreme ends
  • The mean, median and mode all occupy the same midpoint of the curve
165
Q

Define skewed distributions

A

Distributions that lean to one side or the other because most items are either at the lower end or higher end of the distribution

166
Q

Describe negative skews as a way of presenting quantitative data

A
  • Most of the distribution is concentrated towards the right end of the graph, resulting in a long tail on the left
  • e.g. a very easy test in which most people get high marks would produce a negative skew
  • The mode is the highest point of the peak, the median comes next and the mean is dragged across to the left
167
Q

Describe positive skews as a way of presenting quantitative data

A
  • Most of the distribution is concentrated towards the left of the graph, resulting in a long tail on the right
  • e.g. a very difficult test in which most people get lows marks would produce a positive skew
  • The mode is the highest point of the peak, the median comes next and the mean is dragged to the right
168
Q

What does percentage mean?

A

Divide by 100

169
Q

How do you work out percentage to a decimal?

A
  1. Remove the % sign
  2. Move the decimal point 2 places to the left
170
Q

What are decimal places?

A
  • Number of digits to the right of the decimal point
  • e.g. 0.00045 is four decimal places
171
Q

How do you work out decimals to a fraction?

A
  1. Work out the number of decimal places in your number
  2. If there are 2 decimal places, then the denominator is 100 etc.
  3. Reduce the fraction by finding the highest common factor - the biggest number that divides evenly into both parts of the fraction
172
Q

Describe ratios

A
  • Expressed as part-to-part ratios or part-to-whole ratios
  • Should always be divided by the highest common factor
173
Q

Describe significant figures

A

A way to simplify very large or very small numbers is by replacing some digits with a 0

174
Q

What is the rule for standard form?

A
175
Q

What are estimates and order of magnitude calculations?

A
  • Estimates - give a number to just 1 or 2 significant figures
  • Order of magnitude - calculate standard form and compare indices
176
Q

How do you substitute values?

A
  • You are given an equation, e.g. a = b + c
  • You are given values for b and c (b = 4, c = 7)
  • What is a? (a = 11)
177
Q

What is significance in statistical testing?

A

The difference or association between 2 sets of data is greater than what would occur by chance i.e. it is a meaningful result

178
Q

What is probability in statistical testing?

A
  • Probability is about likelihood - how likely it is a certain event will happen if the hypothesis is true
  • The accepted level of probability in psychology is 0.05 (5% significance level)
179
Q

How do you find calculated and critical values in statistical testing?

A
  • The researcher uses a statistical test to produce a calculated value
  • The critical values are given in a table of critical values
  • The calculated value is compared with a critical value to decide whether the result is significant or not
180
Q

What 3 things does the researcher need to know to find the critical value?

A
  1. The significance level - usually 0.05
  2. The number of participants in a study (N value) or the degrees of freedom (df)
  3. Whether the hypothesis was directional or non directional (one tailed or two tailed test)
181
Q

How do we know when we should use the sign test?

A
  • If it’s a test of difference (one tailed test)
  • If related data is used (e.g. repeated measures)
  • Data collected is nominal
182
Q

How do you calculate the S value for the sign test?

A
  • The score for Condition B is subtracted from Condition A to produce the sign of difference (either + or -)
  • Add up the number of + and the number of -
  • Participants who achieved the same score in Condition A and Condition B should be disregarded and deduced from the N value
  • The S value is the total of the less frequent sign
183
Q

How do you work out significance with the sign test?

A
  • If S is equal to or less than the critical value, then S is significant
  • The null hypothesis is then rejected and the alternative hypothesis is accepted at the 5% level
184
Q

Outline peer review

A
  • Before publication, all aspects of an investigation are scrutinised by experts (“peers”) in the field
  • These experts should be objective and unknown to the researcher
185
Q

What are 3 aims of peer review?

A
  1. Allocate research funding
  2. Validation of the quality and relevance of research
  3. Improvements and amendments are suggested
186
Q

Peer review protects the quality of published research? How is this a strength?

A
  • Minimises possibility of fraudulent research and ensures research is of the highest quality
  • Preserves the reputation of psychology as a science and increases the credibility and status of the subject
187
Q

Anonymity may be used to criticise rival research. How is this a weakness of peer review?

A
  • A minority of reviewers may use their anonymity to criticise rival researchers
  • Often there is competition for limited research funding, so this may be an issue
188
Q

Discuss the use of public online forums, like Philica, for peer review

A
  • Philica is an open, instant and cheap forum for psychologists to put their work up for review, which opens the research up to a wider cultural demographic
  • There is also no scrutiny if work is being looked at by independent referees
  • HOWEVER, research may be published with many errors without proper peer review
189
Q

There is a risk of publication bias with peer review. How is this a weakness?

A
  • There is a tendency for editors of journals to want to publish “headline-grabbing” findings
  • Means that research that does not meet this criteria is ignored (file drawer problem)
190
Q

Ground-breaking research may be buried with peer review. How is this a weakness?

A
  • Reviewers may be much more critical of research that contradicts their own view
  • Peer review may slow down the rate of change within scientific disciplines
191
Q

What effect does psychological research have on the economy?

A

The findings of psychological research can benefit our financial prosperity

192
Q

How has attachment research into the role of the father affected the economy?

A
  • Recent research has stressed the importance of the father in a child’s healthy psychological development
  • This may promote more flexible working arrangements in the family
  • This means that modern parents are better equipped to contribute more effectively to the economy
193
Q

How has the development of treatment for mental disorders positively impacted the economy?

A
  • A third of all days off work are caused by mental disorders, e.g. depression
  • Psychological research into the causes and treatments of mental disorders means that people have access the therapies or therapeutic drugs, such as SSRIs
  • People with mental disorders can manage their condition effectively, return to work and contribute to the economy

a level psych exams (11 decks)

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