Research methods

• Experimental method

  • It concerns the manipulation of an IV to have an effect on the DV. These can be Field, Quasi, natural.
  • Hypothesis- clearly states the relationship between the variables being investigated. Directional hypothesis- states the direction of the relationships that will be shown by the variables whilst non-directional doesn't.
• Example of directional and non directional hypothesis

  • E.g. if researcher is carrying out study to investigate whether sleep helps memory performance. For directional hypothesis- More sleep participant has, better their memory performance.
  • Non directional- Difference in amount of hours of sleep a ppt has will have an effect on their memory performance, which will be shown by the difference in memory test scores of ppts.
• Directional and non-directional Hypothesis (2)

  • Directional tends to be used when there's already been range of research carried out which relates to the aim of researcher's investigation. Data from previous research would suggest particular outcome.
  • But if there's no previous research carried out related to study's aim, than non-hypothesis is appropriate.
• Operationalisation of variables

  • clearly defining variables in terms of how they are being measured.
  • The hypotheses states should also show this operationalisation e.g. the aforementioned directional hypothesis would be even better if operationalised.
  • E.g. ppts getting at least 4 hrs of sleep will have better performance on memory tests, shown by achieving higher scores than the ppts that got less than 4 hrs sleep.
  • This could be further operationalised when more details of investigation is given such as number of questions in the test, hence the maximum score ppt can achieve.
• Extraneous variables

  • The only aspect that shoudl effect the DV is the IV, any other shoudl be controlled or removed from the experiment.
  • refers to any other variables which isn't the IV that affects DV and doesn't vary systematically with the IV.
  • Examples are the lighting in lab or the age of ppt
  • These variables don't confound the results of a study but just make them harder to detect.
• Confounding variables

  • Variable other than IV which has an effect on DV.
  • Unlike extraneous, CF doesn't change systematically with the IV
  • With these variables it becomes difficult for researchers to be sure of origin of the impact on DV as CF could be the cause
  • E.g. the sleep study would be time of the day the experimental task was done- those who complete memory test later on day- more tired, therefore do worse, obscuring the true relationship between lack fo sleep and memory performance.
  • So CF variables must be controlled, identified-so ppts should take tests at the same time in the day.
• Demand characteristics

  Any cue the researcher may give which makes the ppt feel like they can guess the aim of the investigation.

  They may change their behaviour to fit in the situation rather than acting naturally known as ppt reactivity.

  Ppt reactivity may lead to investigator effects which refers to unwanted influence from researcher's behaviour either conscious/unconscious on the DV measured including factors like interaction between each ppts in the research investigation, design of study.
• Randomisation and standardisation

  • To minimise effects of extraneous and confounding, different steps can be taken by researcher like randomisation/standardisation.
  • Randomisation- use of chance to reduce the effects of bias from investigator effects, can be done for design of materials, deciding order conditions like selection of ppts
  • Standardisation- using the exact same formalised procedures and instructions for every single ppt involved in research process, this allows there to eliminate non-standardised instructions as being possible extraneous.
• Experimental method- Type of experiment

  Lab- experiment takes place in special environment whereby different variables can be carefully controlled. Strength- high degree of control as experimenters control all variables, Iv has been precisely replicated, leading to greater accuracy, replication- researchers can repeat experiments and check results.

  Limitations- Experimenter's bias, this bias can affect resultsand ppts may be influenced by these expectations.

  Low ecological validity- high degree of control, makes situation artificial , unlike real-life
• Field experiment

  • experiment conducted in a more natural environment, not in lab variables still being controlled.
  • Strength- naturalistic- so more natural behaviours hence high ecological validity, controlled IV.
  • Limitation- ethical considerations, invasion of privacy and likely to have been informed consent.
  • Another limitation- lack of control over extraneous hence precise replication not possible.
• Quasi


  Experiment which IV has not been determined by the researcher, instead it naturally exists e.g. gdifferenceender studies.

  Strengths- controlled conditions - hence replicable, likely to have high internal validity.

  Limitation- cannot randomly allocate ppts- to conditions so there may be CF variables presented. This makes it harder to conclude that the IV caused the DV.
• Natural experiment

  • The experiment in which IV isn't brought about by researchers hence would've happened even if researchers hadn't been there e.g. studying reactions to earthquakes.
  • Strength- provide opportunities for research that otherwise would be impossible due to practical, ethical reasons.
  • Another strength- high external validity as dealing with real life issues.
  • Limitation- Natural occurring events- rare means experiments are unlikely to be replicable,hard to generalise findings
  • Another limitation- very difficult to randomise ppts into groups so CF,extraneous become a problem.
• Oppurtunity sampling 


  ppts happen to be available at the time which the study is being carried out so are recruited convienently

  Strength- easy method of recruitment, time saving and less costly.

  Limitations- Not representative of whole population hence lacks generalisability. Researcher bias is presented as they control who they want to select
• Random sampling 


  When all members of the population have equal chances of being the one selected, each member assigned a number and random number generator is used to randomly choose someone.

  Strength- No researcher bias as researcher has no influence as to who is picked.

  Limitation- Time consuming as need to have list of members of ppulation and contacting themtakes time. Volunteer bias- ppts can refuse to take part so can end up with an unrepresentative sample.
• Systematic sampling

  • Predetermined system is used whereby every member is selected from the sampling frame.
  • This numerical selection is applied consistently
  • Strength: Avoids researcher bias and usually fairly representative of population.
  • Weakness: Not truly unbiased unless you use a random number generator and then start the systematic sample.
• Stratified sampling

  • composition of the sample reflects varying proportions of people in specific subgroups (strata) within wider population.
  • First identify strata, calculate required proportion needed for each stratum based on target population.
  • Then select sample at random from each stratum- random selection method.
  • Strength- no researcher bias, produce representative data due to the proportional strata so generalisation is possible.
  • weakness- time consuming to identify strata and contact person from each. Identfied strata can't reflect all differences between people of wider population
• Volunteer sampling

  • involves self selection whereby the ppt offers to take part in either response to an advert or when asked to do it.
  • Strength- Quick access to wiling ppts which makes it easy, not time-consuming. As ppts are willing to take part, they are more likely to cooperate in study.
  • Weakness- volunteer bias as study may attract particular profile of person means generalisability is affected. Motivations like money- could be driving participation so ppts may not be taking study seriously, influencing results
• Experimental design- Independent group design

  • ppts only performin one condition of IV
  • Strength- no order effects presented. Ppts are less likely to guess aims of study (demanded characterstics are eliminated.)
  • Limitation- no control over ppt variables whereby different abilities of ppts in various conditions can cause changes to DV, you need more ppts than other designs to gather the same amount of data.
  • Solution- Random Allocation solves the first limitation mentioned ensuring each ppt has same chance of being in one condition of the IV as another.
• Repeated measures

  • same ppts take part in all conditions of the IV.
  • strength- eliminates ppt variables, fewer ppts needed so not as time consuming finding and using them.
  • Limitations- Order effects presented e.g.boredom may mean in second condition done ppt does not do well on task.
  • solution- counterbalancing, when half of ppts do conditions in order and the other half do it in an opposite order.
• Matched pairs

  • pairs of ppts are first matched on some variable that has been found to affect DV then one member of each pair does one condition and the other does another.
  • Strength- No order effects, demand characteristics are less of a problem.
  • Limitation- time consuming andf expensive to match ppts, a large pool of potential ppts is needed which can be hard to get, difficult to know which variables are appropriate for the ppts to be matched.
• Pilot studies

  • pilot study is a small-scale version of an investigation which is done before the real investigation is undertaken, carried out to allow potential problems of the study to be identfied
  • This allows money and time saved in the long run.
• Pilot studies- Single and blind procedure, 


  Single-blind: where researchers don't tell ppts if they are given a test treatment/control treatment, done by ensuring ppts don't bias the results - avoids demand characteristics.

  Double-blind: Procedure in where experimenter, ppts don't know who is receiving particular treatment- used to prevent bias in research results.

  Control/condition group- sets baseline whereby results experiments from experimental condition can be compared to results from this one, if there is significantly greater change in experimental group
• Pilot studies- control/condition group

  • Control/condition group- sets baseline whereby results experiments from experimental condition can be compared to results from this one
  • if there is significantly greater change in experimental group compared t0o the control than the researcher is able to conclude that the cause of effect was the IV
• Correlations

  • technqiue used to investigate an association between two variables- co-variables.
  • The variables are simply measured not manipulated like experiments, only an association is found so no cause-and- effect found hence DV,IV not used.
  • Correlation coefficients determines strength and the relationship between 2 variables.
• Varoius relationships shown between co-variables

  • Negative correlation- when onevariable increases the other decreases,has negative gradient, has correlation coefficient of less than 0.
  • Positive correlation- when one variable increases the other also increases, positive gradient, has correlation coefficient more than 0.
  • Zero correlation- no relationship found between co-variables, no line of best fit can be drawn as points are at random, has correlation coefficient of 0.
• Cuvilinear relationship

  • as one variable increases so does the other but only up to certain point after which as one variable continues to increase the other begins to decrease.
  • On graph forms inverted U shape.
  • E.g. directional hypothesis states whether there will be a negative/positive correlation between the co-variables being studies whilst non-directional hypothesis only states there will be a correlation but the type is unknown.
• Strength and limitation of correlations

  • Strengths: can be used as starting points to assess patterns co-variables before committing to conducting an experimental study. Quick ,economical to carry out, secondary data can be used in correlational study- makes it even less time consuming.
  • Limitations: difficult to establish cause-and-effect relationship. Third variable problem presented as there's chance of another variable, researcher is unaware of it and its responsible for relationship between co-variables. Correlations can be misinterpreted, often presented as causation.
• Observational techniques


  Naturalistic- watching and recording behaviours in the settings it would normally take place.

  Strength: High ecological validity, High external validity as it's done in an natural environment.

  Limitations: Low ecological validity if ppts become aware they are being watched, replication can be difficult, Uncontrolled confounding and extraneous variables are presented.
• Controlled observation

  • Watching and recording behaviour in a structured environment e.g. lab setting.
  • Strength: Researchers are able to focus on a particular aspect of behaviour, there's more control over extraneous and confounding variables, easy replication.
  • More likely to observe unnatural behaviour as it takes place in an unnatural environment.
  • Low mundane realism so low ecological validity, demand characteristics presented
• Overt Observation

  • ppts are watched and their behaviour is recorded with them knowing they are being watched.
  • Strengths: Ethically acceptable as informed consent is given
  • Limitation- ppt know they are being observed, demand characteristics which reduces validity of findings.
• Covert observation

  • ppts are unaware that their behaviour are being watched and recorded
  • Natural behaviour recorded hence high validity of results, removes problem of ppt reactivity whereby ppts try to make sense of the situation they are in, making them easily guess aim of the study.
  • Limitations- ethical issue as no informed consent given, also could be invading privacy of ppts.
• Ppt observation

  • researcher who is observing is part of the group that is being observed.
  • Strength: can be more insightful which increases validity of findings.
  • Limitations- always possibility that behaviour may change if ppt found out they are being watched, researcher may lose objectivity as they may start to identify too strongly with ppts
• Non-ppt observation


  Researcher observes from a distance so is not part of the group being observed

  Strength: researcher can be objective as less likely to identify with ppt since watching outside of the group

  Limitation- Open to observer bias for example of stereotypes the observer is aware of, researcher may lose some valuable insight.
• Observational designs

  • One problem of carrying out observations- observer bias is easily presented as their reports may be bias by what they expect to see, solution to this is to check the inter observer reliability of observation which is done by many researchers conducting observational study
  • Their reports are then compared and score is calculated using total number of agreements/total number of observations x 100
  • The score showing high inter observer reliability is any score above 80%.
• Observational designs- Unstructured design

  • consists of continuous recording where a researcher writes everything they see in observation
  • Strength: More richness and depth of detail
  • Limitation: Produces qualitative data which is more difficult to record and analysis, greater risk of observer bias e.g. only record catch the eye behaviours.
• Structured design

  • researcher quantifies what they are observing using predetermined list of behaviours and sampling methods.
  • Strengths: easier as its more systematic
  • Quantitative data is collected which is easy to analyse and compare with other data and less risk of observer bias.
  • Limitations- not much depth in detail, difficult to achieve high inter observer reliability as filling the predetermined lists in is subjective.
• Behavioural strategies used whilst conducting structured observations.

  • When target behaviour is being observed is broken up into more precise components which are observable and measurable e.g. aggressive behaviour can be broken down to shouting, punching.
  • When forming behavioural strategies, it's important to make sure that behaviours don't overlap with other behaviours so very similar behaviours should not be listed e.g. grin and smile.
  • Should be clearly operationalised
• Structured interviews- different types of sampling methods

  Time sampling- the recording of behaviour within a time frame that pre-established before the observational study.

  Strength: reduces number of observations that has to be made so less time-consuming.

  Limitation- the small amount of data collected within the time-frame ends up being unrepresentative of the observation as a whole.
• Different sampling methods- Event sampling

  • involves the counting of number of times of particular behaviour is carried out by the target group.
  • Strength: good for infrequent behaviours that are likely to be missed if time sampling was used.
  • Limitation- if complex behaviour is being observed, important details of behaviour may be overlooked by observer, if the behaviour is very frequent there could be counting errors, it is difficult to judge the beginning and ending of a behaviour.
• Types of data- qualitative data

  • qualitative- which is displayed in words, non-numerical.
  • Strength: more richness and depth of detail, allows ppt to further develop their opinions hence has greater external validity, more meaningful insight into ppts views achieved.
  • Limitation: difficult to analyse and make comparisons with other data, researcher bias presented as conclusions rely on subjective interpretations of researcher- interpreter bias.