Research Methods Psychology

  1. What is a laboratory experiment?
    The independent variable is the one which is manipulated by the experimenter in a controlled environment.
  2. What is a field experiment?
    Experiments conducted in the natural environment of the participants in which the independent variable is still manipulated by the experimenter.
  3. What is a quasi experiment?
    These may take place in laboratories or in everyday settings.

    The independent variable is naturally occuring.

    Not considered a 'true' experiment as the IV is not manipulated
  4. What do all experiments involve?
    Experiments always involve looking for a difference between conditions.
  5. What is the IV?
    The Independent Variable is the variable which is manipulated
  6. What is the DV?
    The dependent variable is the variable which is measured
  7. What are the advantages of laboratory experiments? (2)
    1. The setting allows for control of extraneous variables so the experimenter can infer a cause-effect relationship between the IV and the DV.

    2. The setting allows for standardisation of procedures so that variables can be kept constant (the same for all Ps)
  8. What are the weaknesses of laboratory experiments? (2)
    1. Participants may behave differently in laboratories than in natural environments so demand characteristics and investigator effects may affect the results

    2. Practically difficult (if not impossible) to create a laboratory scenario which reflects everyday life so the results may lack ecological validity.
  9. What are the advantages of field experiments?(2)
    1. Behaviour is taking place in a real environment therefore the results are more ecologically valid

    2. There will be no demand characteristics as observer effects are less likely to occur. Demand characteristics may occur when the participant knows they are involved in research and try to guess what the researcher expects of them by picking up cues from the researcher.
  10. What are the disadvantages of field experiments? (2)
    1. There is a lack of control and standardisation over the research setting which make replication difficult and then may cause problems with reliability of the results (consistency).

    2. It may be practically difficult/unethical for researchers to gather data unobtrusively
  11. What are the advantages of quasi experiments?
    1. This method can be conducted in either a lab or a field depending upon what is being investigated

    2. This method can point to a cause and effect relationship in rare or atypical behaviours that are otherwise difficult to study
  12. What are the disadvantages of quasi experiments? (2)
    1. The IV is naturally occurring so participants cannot be randomly allocated to conditions therefore participant variables are uncontrolled and can confound results (unless a matched pairs design is used)

    2. It may be practically difficult to find the naturally occurring IV due to its rarity
  13. What is independent measures design?
    Participants are placed in different conditions
  14. What is repeated measures design?
    Here, participants are placed in all the conditions

    example; participants perform a task with music and then again without music
  15. What is counterbalancing?
    Counterbalancing is used in repeated measures design to prevent participants from getting better/worse when performing a task the second time.

    It is where half the participants perform the tests in one order and the other half of Ps perform tests in the opposite order.
  16. What is matched pairs design?
    All participants are pre-screened on any variables which may affect their performance on their task and matched in pairs across the different conditions

    example: If the task is a memory test, a pre-test on memory will be conducted. Take the 2 highest scorers on memory and place them in the music condition and in the silent condition. Then do the same for the next 2 highest scorers and so on...
  17. What are the advantages of independent measures design? (2)
    1. Quicker to be carried out than repeated measures design so recruiting participants may be faster

    2. Participants may be less likely to guess the aim of the research than with repeated measures because they only experience one condition as they experience all the conditions in repeated measures design
  18. What are the disadvantages of independent measures design? (2)
    1. May be hard to keep all variable constant across conditions so unwanted situational variables may affect the results

    2. There will always be uncontrolled participant variables which may confound results and reduce validity
  19. What are the advantages of repeated measures design?
    1. Same participants in each condition therefore no participant variables are affecting results therefore validity will be higher

    2. Simple strategies (e.g. counterbalancing) can be used to control for possible order effects
  20. What are the disadvantages of repeated measures design?
    1. Participants may suffer from boredom or fatigue or become practised at tasks; these order effects may confound results and reduce validity.

    2. Participants are more likely to guess the hypothesis; therefore results may be affected be demand characteristics therefore validity will be reduced
  21. What are the advantages of matched pairs design? (2)
    1. Reduces the effects of some key participant variables therefore increases validity

    2. No order effects so validity will be higher
  22. What are the disadvantages of matched pairs design?
    1. Practically difficult to do this and takes a long time, meaning fewer participants may be tested therefore the results could be less generalisable

    2. Requires twice as many participants as one of the other designs so again, may be fewer participants
  23. What is important when determining a cause-effect relationship?
    That other variables other than the IV are not affecting the DV
  24. What is meant by 'internal validity'?
    The extent to which factors other than the IV may be affecting the measure of behaviour
  25. What is an extraneous variable?
    Variables that may affect participants which differ from the IV
  26. What affects the validity of an experiment?
    • V for Validity
    • V for extraneous Variables
  27. What is meant by the 'reliability' of a study?
    It concerns whether the results in the study can be repeated or not
  28. What are the different types of validity? (8)
    • Face
    • Construct
    • Concurrent
    • Criterion
    • External
    • Population
    • Ecological
  29. What are participant variables?
    Any personal characteristics of participants which are likely to influence the DV other than the IV
  30. What is meant by the term 'researcher effects'?
    Any environmental factor other than the IV that can affect a participant's performance such as lighting, temperature, room layout, noise
  31. What is a demand characteristic?
    Where participants try to find out how the researcher expects them to behave and they often pick up on cues form the psychologist on how to behave.

    Participants may also guess what is expected of them from the task that they have been given - problematic for psychologists use psychology students as their participants this is because they already have knowledge/interest about the subject so they have an idea of what they are trying to find out
  32. What is participant reactivity?
    When the participant responds to the experimental situation in an artificial way
  33. What is an 'order effect'?
    Where psychologists use the same participants in both the experimental and control conditions - (known as repeated measures design) this may participants to become more practised at a task so they may be better doing it the second time around
  34. What is meant by the term 'researcher effects'?
    Researches have expectations about the outcome of an experiment and this can become a source of bias.
  35. What is random error?
    These errors or unwanted variables are due to factors that are not predictable and as result it is not easy to reduce their effect.

    E.g. a participant may be unwell on the day of the experiment but may still take part. Their illness however could affect their performance. Or, as participants perform their task a fire alarm may go off and interfere with their concentration.
  36. What is standardisation?
    This is a control which refers to keeping things the same for all the participants
  37. What do extraneous variables affect?
    Validity of the results
  38. How do you control for participant variables?
    • Random allocation of participants to conditions
    • Screening participants before they participate by asking them questions for example
    • Use the SAME participants in all conditions so they are in effect being compared with themselves (repeated measures) or use matched pairs design
  39. How do you control for situational variables?
    • Use lab setting
    • Standardisation  means keeping everything the same for all the participants. e.g. standardising instructions instructions/amount of time given to participants to perform a task and using a standardised procedure for all the participants.
  40. How do you control for demand characteristics? (4)
    • Deceive participants about the aim
    • Keep participants naïve about the aim - 'single blind technique'
    • Use distraction tactics - e.g. include irrelevant questions on a questionnaire
    • Use a field setting in which participants are unaware of their involvement in the study
  41. How do you control for investigator effects? (2)
    1. Use a third party who is unaware of the aim to test participants - ‘double blind technique’**

    2. Ensure researcher is unaware which condition participants are in – ‘double blind technique’
  42. How do you control for random error?
    Random error cannot be controlled
  43. How do you control for order effects? (3)
    • Use different participants in each condition (independent measures design)
    • Use a time break between the conditions
    • Counterbalance so some participants do condition A then condition B and the others do condition B and then A (ABBA)
  44. What is the problem with a self-selected sample?
    Participants may try to guess the aim of the experiment and then tailor their behaviour around that aim
  45. What is it about a volunteer that makes demand characteristics more likely?
    They have an interest for the subject so have more knowledge as they are putting themselves forward and these are the type of people that want to help. You only have a sample formed up of volunteers making it unrepresentative.
  46. Which design is more likely to cause demand characteristics? Repeated measures or Independent Measures? Why?
    Repeated measures because they will experience the different conditions making it more likely for them to guess the aim of the experiment
  47. What is an 'aim' to an experiment?
    This tells us why the research is taking place
  48. What is a hypothesis?
    A hypothesis is a testable statement in which the variables are clearly stated in measurable terms.

    This is called operationalising variables.
  49. What does the word 'significant' tell us when used in a hypothesis?
    This tells us that the data from the research will be analysed using a statistical test
  50. What is a feature of a one-tailed (directional) hypothesis?
    The hypothesis will specifically predict how the independent variable will affect the dependent variable
  51. What is a feature of a two-tailed (non directional) hypothesis?
    The hypothesis is not specific in the direction of the results. It predicts that there will be a change occurring in result of the independent variable but does not tell what the direction of that change will be.
  52. How do you write a two-tailed hypothesis?
    It is predicted there will be a significant difference in (the DV) between (condition A of the IV) and (condition B of the IV)
  53. What is an alternate hypothesis?
    With some types of non-experimental research (e.g. correlations and observations), researchers may not be predicting casual relationships, instead, they might predict a pattern or an association between the two variables.
  54. Why does a null hypothesis need to be created?
    The experimenter must also create a null hypothesis alongside either a experiment or alternate hypothesis because for research to be considered 'scientific', the hypothesis should be capable of being shown to be wrong.
  55. How do you write a null hypothesis?
    There will be no significant difference (in the DV) between (condition A of the IV) and (condition B of the IV). Any difference found will be due to chance.
  56. What should the null hypothesis state?
    That any difference found between two sets of data has not been caused by the IV, or that correlations or associations shown in the data are not meaningful (significant).
  57. What are participants?
    People who take part in the research
  58. What is a target population?
    The population from which the participants are drawn
  59. Why do experimenters use sampling techniques?
    In order to chose people who are representative of the target population as a whole
  60. What can you do if you have a representative sample?
    You can generalise the results to the wider population
  61. Why is it important to gather a large sample?
    reduce bias from any atypical individuals
  62. What is opportunity sampling?
    It consists of taking the sample from people who are available at the time the study is carried out and fit into the criteria you are looking for.
  63. What are the strengths of opportunity sampling?
    • 1. Quick and easy to obtain participants
    • 2. Participants are very willing to participate
  64. What are the weaknesses of opportunity sampling?
    • Such samples are often biased
    • Participants may share many variables in common with the researchers
    • Participants may want to please the investigator who are known to them
  65. What is a random sample?
    This is a sample where every member of the population has an equal chance of being chosen.

    This involves identifying everyone in the target population and then selecting the number of participants you need in a way that gives everyone in the population an equal chance of being chosen
  66. What is a strength of random sampling?
    The sample will be representative of the target population
  67. What is a weakness of random sampling?
    • It is very difficult to obtain a truly random sample.
    • Researchers may not have details of ALL the people in their target population
    • Most psychological research does not use random sampling
  68. What is a self-selected (volunteer) sample?
    This consists of participants becoming part of a study because they volunteer when asked or in response to an advert
  69. What is a strength of self-selected sampling?
    • It is useful as it is quick and relatively easy to do.
    • It can reach a large number of participants and is ethical as by volunteering, they are giving some degree of consent (although this may not be fully informed)
  70. What is a weakness of self-selected sampling?
    The type of participants who volunteer may not be representative of the target population for a number of reasons.

    e.g. they may be more obedient, more motivated to take part in studies etc. Also, they may be people who happen to access a certain publication or location where the advert was posted (e.g. all may visit their local library and read what is on the notice board)
  71. What is snowball sampling?
    When participants are hard to find, or when the researcher need a particular kind of person, one way to obtain more participants is to ask those participants you already have to find further participants
  72. What is an advantage of snowball sampling?
    • Relatively easy as you only have to find the first few.
    • A convenient way to find a sample of a particular kind of participant.
  73. What is a weakness of snowball sampling?
    Non-representative as they are likely to be similar in ways other than any common characteristics needed for the study
  74. What is population validity?
    the extent to which findings from one sample can be generalised to the whole of the population from which the sample was taken, and to other populations.
  75. What is external validity?
    This relates to issues beyond the investigation and therefore includes population validity and ecological validity
  76. What is internal validity?
    relates to the issues within the investigation
  77. What does validity concern?
    the extent to which you will be certain your dependent variable is actually measuring what you intended it to measure
  78. What will uncontrolled variables affect?
    dependent variable
  79. What is face validity?
    whether a measure appears, at face value, to actually be measuring what it says it is.
  80. What is criterion validity?
    whether a phenomenon measured in one way will relate to another (related) variable e.g. you should always use a tape measure to measure length
  81. What is concurrent validity?
    a type of criterion validity and concerns whether a measure will produce a similar score for a particular individual as another test that claims to assess the same phenomenon
  82. What is construct validity?
    Looking at whether a measure is based on some certain-to-exist phenomenon, which it is testing.
  83. Where does construct validity arise from?
    Where theoretical and empirical research are combined together
  84. What is ecological validity?
    a type of generalisability

    the extent to which research results can be generalised to behaviour in everyday life, especially as so many studies are performed in artificial lab situations
  85. What is a pilot study?
    These are studies conducted once a study has been designed but before data is gathered.

    They tend to be a small scale 'dry-run' of the proper study and provide an opportunity for the researcher to try out planned procedures and adjust the design if necessary.
  86. Why are pilot studies a good idea? (2)
    • 1. They increase validity as they ensure that behaviour is being measured appropriately
    • 2. They increase reliability as any problems that might lead a replication to find different results to the original are ironed out
  87. What are the four types of data?
    • Primary data
    • Secondary data
    • Qualitative data
    • Quantitative data
  88. What is primary data?
    This is the data that has been collected directly from the participants and has not been manipulated
  89. What is secondary data
    This is where the researcher uses data that has already been conducted by someone else, this may be reanalysing another psychologists data, or even using data collected for a different purpose

    e.g. a schools exam results which you then might correlate with other data
  90. What is quantitative data?
    focuses on numbers and frequencies - objective data

    Qualitative methods; e.g. experiments, questionnaires and psychometric tests
  91. What is qualitative data?
    concerned with describing meaning rather than drawing statistical inferences

    Qualitative methods e.g. case studies and interviews
  92. What are the strengths of quantitative data?
    • Tends to be collected using objective measures
    • Data collection tends to be highly reliable
    • Data can be analysed using inferential statistics (in standardised ways) meaning comparisons can be made and conclusions can be drawn. Also, it can tell us how likely our results occurred due to chance (rather than an independent variable).
    • It tends to be objective and doesn't require the same degree of interpretation that qualitative data requires - higher in reliability than in qualitative data
    • It allows us to identify patterns and trends quickly e.g. scattergrams
  93. What are the weaknesses of quantitative data?
    • May lack validity because it limits participant's responses e.g. if appropriate response options are not available
    • It often lacks detail as it reduces some aspects of human behaviour down to simple numbers and so some of the richness and complexity of that behaviour is lost
    • it often tells us what occurred but not why it occurred
  94. What are the strengths of qualitative data?
    • Data collection may be highly valid as it is likely to be possible for participants to express themselves exactly as they want to - this subjectivity should protect the validity of the data because an investigator is not imposing their interpretation on it
    • It is less likely that key or rare observations will be 'lost' through the process of averaging or simplifying data
    • It provides lots of rich detail which can give in-depth insights into such things as reasons for behaviour
    • It is generated in natural social contexts so actions are more meaningful
  95. What are the weaknesses of qualitative data?
    • Qualitative data is not easy to analyse - it is therefore not considered as 'scientific' as quantitative data
    • Though possible, it is more difficult to draw comparisons between participants when qualitative data has been gathered
    • Qualitative data usually involves personal accounts which may be biased and possibly invalid due to many factors.  e.g. participants feeling embarrassed by the sensitive nature of the questions. they may respond to social desirability or other researcher effects
    • The gathering of qualitative data may be time consuming
  96. What is nominal data?
    Simplest and least descriptive type of numerical data; a frequency count where categories are used.

    The mode is used to find the average

    Key things to consider;

    • A numerical value often cannot be assigned to these categories
    • Each participant can only be placed in one category
    • Normally expressed as percentages
    • Observations and content analyses yielding tallies are where psychologists clearly have nominal data
  97. What is ordinal data?
    This data is where a numerical value is used but is based on ranks and ratings. It is subjective as it is based on a person's own personal opinion which may not be correct.

    The median is used to find an average


    • self-report questionnaires
    • likert scale (participants are given a statement and asked to state their level of agreement)
  98. What is interval data?
    Concerns fixed and publicly agreed units of measurement e.g. weight, temperature, speed etc.

    Data is in the form of equal units e.g.score on an objective test

    It is objective and based on facts and not opinions

    The mean is used to find an average

    Note - data is only interval data if items are of similar level of difficulty
  99. What are the strengths of nominal data?
    Useful information
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Research Methods Psychology
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