Research methods

• "The experimental method"


  Involves manipulating one variable to determine if these changes cause changes in another variable. This method relies on high levels of control to test a hypothesis
• Research aim

  An general statement about what the researcher intends to investigate; the purpose of the study
• in psychology, independent variables can also change naturally

  dependent - measured and should be caused by independent
• operationalise

  to be clearly defining your variables
• operationalised:

  • number of words accurately recalled
  • reaction time in seconds
  • number of faces accurately recognised
• not operationalised:

  • punishment given (define types of punishment)
  • intelligence level (iq level)
  • resources selected (define)
• hypothesis

  states what you believe is true. its precise and testable statement of the relationship between 2 variables. it's a statement not a question or prediction. directional or non-directional.
• non directional hypothesis


  states that there is a difference between two conditions or two groups of people in a precise and operationalised without stating what the difference will be
• directional hypothesis


  states the direction of predicted differences between two conditions or two groups of people in a precise and operationalised way.

  this hypothesis can only be used when there has been previous research.
• all experiments

  • experiments allow us to study cause and effect (causation). they all have an IV (independent variable) and a DV (dependent variable) and make some attempt to control all other potential extraneous variables (EVs)
  • there are 4 kinds of experiments:

  1. lab
  2. field
  3. natural
  4. quasi
• experimental designs

  • experimental designs are only used for experimental methods - lab, field, natural, quasi
  • most simple experiments involve 2 conditions - these are 2 versions of the independent variable. eg, using words or pictures to learn a list of items
  • there are 3 different ways to carry out the experiment with participants. these are known as the experimental designs:

  1. independent measures design
  2. repeated measures design
  3. matched pairs design
• independent measures design


  one group does condition A and a second group does condition B.

  participants should be randomly allocated to experimental groups
• independent measures design- evaluation

  strengths:

  • no order effects. participants are only tested once so cant practice or become bored/tired. this controls an important CV
  • will not guess aim. participants are only tested once so are unlikely to guess the research aims. therefore behaviour may be more 'natural' (higher realism)

  weaknesses:

  • participants variables. the participants in the two groups are different, acting as EV/CV. may reduce the validity of the study
  • less economical. need twice as many participants as repeated measures for same data. more time spent recruiting which is expensive
• repeated measures design


  same participants take part in all conditions of an experiment. the order of conditions should be counterbalanced to avoid order effects
• matched pairs design

  two groups of participants are used but they are also related to each other by being paired on participant variable(s) that matter for the experiment
• sampling: population


  a large group you are interested in studying. if it is quite a specific group of people eg, children with autism under 6 years, this is a target population
• within the target population the researcher will take an even smaller group of people called the sample eg, 20 children under 6 with children

  psychologists do this, hoping the sample will be representative of the target population so their results could be applied or generalised to them.
• types of experiment


  1. lab
  2. field
  3. natural
  4. quasi
• lab experiment


  an experiment that takes place in a special environment whereby different variables can be carefully controlled

  strengths:

  • high degree of control - experimenter controls all variables, the IV has been precisely replicated, leading to greater accuracy
  • replication - researcher can repeat experiment and check results

  weakness:

  • experimenter's bias - this bias can affect results and participants may be influenced by these expectations
  • low ecological validity - high degree of control makes the situation artificial, unlike real life
• natural experiment


  occurs in participants natural setting that requires no manipulation by the researcher. researcher has little control over the conditions of experiment

  strengths:

  • provides opportunities for research that would have otherwise been impossible due to practical/ethical reasons
  • high external validity - dealing with real life issues

  limitations:

  • natural occurring events may be rare but this means experiments are not likely to be replicable hence hard to generalise findings
  • very difficult to randomise participants into groups so cofounding and extraneous variables become a problem
• quasi experiment


  an experiment whereby the IV has not been determined by the researcher instead it naturally exists eg, gender difference studies

  strengths:

  • controlled conditions - replicable, likely to have high internal validity

  limitations:

  • cannot randomly allocate participants to conditions so there may be cofounding variables presented. this makes it harder to conclude that the IV caused the DV
• sampling techniques


  • target population
  • random sampling
  • opportunity sampling
  • stratified sampling
  • volunteer sampling
  • systematic sampling
• target population


  the entire population, or group, that a researcher is interested in researching and analysing.

  strengths:

  • clear focus = well defined population help stay focused on research question
  • accurate representation = sample accuracy reflects population characteristics
  • if sample is representative and accurate then findings can be generalised to larger population

  weaknesses:

  • bias sample = poor defined population lead to sample bias = groups under/overpresented = affects accuracy
  • finding not generalised to larger population
• random sampling


  every member of a population has the same chance of being selected for study.

  strengths:

  • no researcher bias = researcher has no influence on who is picked - no bias / personal judgement
  • samples representative of population = findings are more generalisable

  weaknesses:

  • time consuming = need list of members of population (sampling frame) and contacting them takes time
  • volunteer bias = participants can refuse to take part = end up with unrepresentative sample
• opportunity sample


  researcher selecting anyone who is available and willing to take part in the study.

  strengths:

  • easy method of recruitment = saves time and less costly
  • allows access to participants who are ready and available to participate

  weaknesses:

  • not representative of whole population = lacks generalisablilty
  • researcher bias = control who they want to select
• stratified sampling

  researchers divide subjects into subgroups called strata based on characteristics that they share

  strengths:

  • no researcher bias = selection within each stratum is done randomly
  • produces representative data due to the proportional strata = increased generalisability

  weaknesses:

  • time consuming = identify and contact each strata
  • identified strata cannot fully represent the target population due to inability to account for all differences among the wider population
• volunteer sampling

  an approach where participants willingly contribute their thoughts and experiences.

  strengths:

  • quick access to willing participants = no time consuming
  • participants more likely to cooperate in the study

  weaknesses:

  • bias = volunteers may not be representative to population = limits generalisability
  • money motivates more participants = not taking study seriously = influencing results
• systematic sampling

  a sampling technique that uses a predetermined system to select the participants from a target group.

  strengths:

  • avoid researcher bias
  • fairly representative of population

  weaknesses:

  • if population is not identical = may not produce representative sample = limits generalisability
  • if a pattern = biased sample
  • less random than random sampling = affect precision of estimates
• what is a correlation?


  this is a relationship between two variables. there is no IV or DV in these types of studies
• correlation coefficients


  • this is a number, eg, +0.76 or -0.76
  • the maximum coefficient is 1.0 (1.0 = a perfect positive relationship and -1.0 is a perfect negative relationship
  • the coefficient tells us how closely related the variables are
• strengths of correlations


  • shows the relationship between the two variables
  • as with experiments, procedures can be repeated which means findings can be confirmed and there is reliability
  • if the correlation is significant - further research can be done. if it is not significant then you can rule out a simple linear relationship
• weaknesses of correlations


  • cannot remember cause and effect. it only shows a link between the variables
  • there may be a third variable
  • correlations can be misinterpreted. this can have wider implications if results are released to the public
• ethics - developed by British Psychological Society

  code of ethics

  British Psychological Society (BPS)

  1988 - after zimbardo and milgram
• the BPS is the representative body for psychology and psychologists in the uk, and is responsible for the promotion of excellence and ethical practice
• BPS code of ethics


  psychologists in the uk are advised by BPS

  USA = APS

  the most recent code of ethics and conduct identifies 4 key principles:

  1. respect
  2. competence
  3. responsibility
  4. intergrity
• ethical guidelines


  Can Do Can't Do With Participants

  Confidentiality (and privacy)

  Deception

  Consent (informed)

  Debrief

  Withdraw (right to)

  Protection of participants
• informed consent - researchers pov


  means revealing the true aims of the study - or telling participants what will actually happen. however, revealing details might cause participants to guess the aims of the study. eg, is could change the way they behave. therefore, researcher may not always reveal the aims
• informed consent - participants pov


  should be told what they will be required to do so can make an informed decision about if they wish to participate. this is a basic human right, established during the Nuremberg war trials: in WW2, nazi doctors conducted various experiments on prisoners without their consent and the war trials afterwards decided that participants consent should be a right in every study
• informed consent - participants pov (continued)


  even if the researchers have consent, that doesnt guarantee participants understand what they have let themselves in. epstein and lasagna (1969) found that a third of participants really understood what they agreed to take part in.

  another problem is the requirement for researcher to point any likely benefits or risks of participation. researchers are not always able to accurately predict risks or benefits of taking part
• deception - researchers pov


  can be necessary to deceive participants about true aims of the study so they dont alter their behaviour and prevent a meaningless study. however, a distinction should be make between withholding some of the details of aims (reasonably acceptable) and deliberately providing false information (less aceptable)