Research Methods

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  • Created by: Gulnawaz
  • Created on: 12-02-20 17:42

Experimental method

Aim= general expression of what the reseacher intends to investigate.

hypothesisstatement of what the reseacher intends to be true./should be operationlised=clearly defined and measurable./directional hypothesis=whether changes are greater or lesser/non directional=doesnt state direction (there is a difference)

reserchers causes the IV to vary and records the effects of the IV on the DV.

Extraneous variable = are nuisance that do not vary systematically with the IV, reaecher may contol some of these 

Confounding variable = change systematically with the IV so we cannot be sure if any observed change in the DV is due to the CV or the IV. CVs must be controlled.

Demand Characteristic= refers to an cue from the reseacher or research situation that may reveal the aim of the study.

Investigator effects= any effect of the investigators behaviour on the outcome of the reseach the DV

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Research Techniques

Randomisation= The use of chance when designing investigations to control for the effects of bias.

Standardisation= Using exactly the same formalised procedures for all ppts in a reseach study.

Control groups= are used for for the purpose of setting a cpmparison. they act as a baseline and help establish causation.

single blind= a ppts doesnt know the aims of the study so that the demand characteristics are reduced.

Double blind= both ppts and researcher don't know the aims of the study to reduce demand characteristic and investigators effects.

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Independent Groups

one group do condition A and  a second group do condition B. ppts should be randomly allocated to experimental groups.

Strenghts

  • No order effects. ppts are only tested once so can't practice or become bored/tired. this controls an important CV
  • Will not guess aim. ppts only tested once so are unlikely tto guess the research aims. therefore behaviours may be more natural.

weaknesses

  • Ppts variables. ppts in the two groups are different, acting as EV/CV. mat=y reduce the validity of the study.
  • More ppts. need twice as many ppts as repeated measures for same data. more time spent time recruiting which is expensive.
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Repeated Measures

same ppts take part in all conditions of an experiment. the order of conditions should be counterbalanced to avoid order effects.

strenghts

  • Ppts variables. the person in both conditions has the same characteristics. this controls an important CV.
  • Fewer Ppts. half the number of ppts is needed than in independent groups. less time recruiting ppts.

weaknesses

  • Order effects are a problem. ppts may do better or worse when doing a similar task twice. reduces the validity of the results.
  • Ppts may guess aims. ppts may change their behaviour. this may reduce the validity of the results.
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Matched Pairs

Two groups of ppts are used but they are also related to each other by being paired on ppts variables that matter for the experiment.

Strengths

  • Ppts variables. ppts matched on a varaible that is relevant to the experiment. this enhances the validity of the results.
  • No order effects. ppts are only tested once so no practice or fatigue effects. this enhances the validity of the results.

Weaknesses

  • Matching is not perfect. matching is time consuming and can't control all relevant variables. may not address ppts variables.
  • More ppts. need twice as many ppts as repeated measures for same data. more time recruiting which is expensive.
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Types of experiment

 Laboratory experiment= A controlled environment where extraneous and confounding varaibles (EVs and CVs) can be regulated. IV is manipulated and the effects on the DV is recorded.

Strenghts

  • EVs and CVs can be controlled. this means that the effect of EVs and CVs on the DV can be minimised. cause and effect between the IV and DV can be demonstrated (high internal validity)
  • Can be Easily replicated. due to the standardised procedure the experiment can be repeated. if the results are the same this confirms thier validity.

Weaknesses

  • May lack generalisability. the controlled lab environment may be rather artificial and ppts are aware they are being studied. thus behaviour may not be natural and cant be generalised to everday life (low external validity)
  • Demand characteristic may be a problem. these are cues in the experimntal situation that invite a particular response from ppts. The results if the experiment may be explained by these cues rather than the effects of the IV. 

 

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Field experiment

A natural setting. the reseacher goes to ppts. the IV is manipulated and the effect on the DV is recorded.

Strenghts

  • More natural environment. ppts more confortable in their own environment. results may be more generalisable to everyday.
  • Ppts are unaware of being studied. there are more likely to behave as they normally do so the findings can be genaralised. the study has greater external validity.

Weaknesses

  • More difficult to control CVs. observed changes in the DV may not be due to the IV,but to CVs instead.it is more difficult to establish cause and effect than in the lab.
  • There are ethical issues.ppts in a field experiment may not have given informed consent, this is an invasion of ppts privacy, which raises ethical issues.
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Natural experiment

The experiment does not manipulate the IV. The IV would have varied even if the experimenter wasnt interested. DV may be naturally occuring or may be measured by the experimenter.

Strenghts

  • May be the only ethical option. It may br unethical to manipulate the IV, e.g studying the effects of institutionalisation on children.A natural experiment may be the only way casual research can be for such topics.
  • Greater external validity. Natural experiments involve real-life issues,such as the effect of a natural disaster on stress levels. This means the findings are more relevant to real experiences.

Weaknesses

  • The natural event may only occur rarely. Many natural events are one-offs and this reduces the opportunity for research. This may limit the scope for generalising findings to other similar situations.
  • Ppts are not randomly allocated.the experiment has no control over which ppts are placed in which conditions as the IV is pre-existing.May result in CVs that aren't controlled. 
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Quasi-experiment

IV is based on a pre-existing difference between people, e.g. age or gender. no one has manipulated this variable, it simply exists./ DV may be naturally occuring (e.g. exam results) or may be measured by the experimenter.

Strengths

  • There is often high control. often carried out under controlled conditions and therefore shares some of the strengths of lab experiments. this means incresed confidence about drawing casual conclusions
  • Comparisons can be made between people, In a quasi-experiment the IV is a difference between people, e.g people with and without autism. this means that comparisons between different types of people can be made.

Weaknesses

  • Ppts are not randomly allocated. the experimenter has no control over which ppts are placed in which condition as the IV is pre-existing. ppts variables may have caused the change in the DV acting as a CV.
  • Casual relationships not demonstrated. the researcher does not manipulate/control the IV. we cannot say for certain that any change in the DV was due to the IV.
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Sampling

Population= large group of people that a researcher is interested in studying.

Sample= It is usually not possible to include all members of the population in the sudy,so a smaller group is selected.

Generalisation= sample that is drawn should be representative of the population in the study, so genralisation can be made.

Bias= majority of samples are biased in that certain groups may be over-or under represented.

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Opportunity sample

people who are simply most available, i.e. the ones who are nearest/easiest to obtain. HOW?  ask people nearby,e,g, ask the students in your class to take part or ask people who walk past u at a shopping mall.

Strengths

  • Quick method, opportunity sampling is convenient because you just make use of the people who are closest, this makes it one of the most popular sampling methods.

Weaknesses

  • Inevetably biased. the sample is unrepresentative of the target population as it is drawn from a very specific area,such as one street in one town, this means that the findings cannot be generalised.
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Volunteer sample

self-selecting. in a volunteer sample,ppts select themselves. HOW? advertise, e.g. place an ad in a newspaper or on a noticeboard and ppts come to you.

Strengths

  • Ppts are willing. ppts have selected themselves and know how much time and effort is involved, likely to engage more than people stopped in the street.

Weaknesses

  • Likely to be a biased sample, ppts may share certain traits, e.g. keen and curious. Generalisation limited due to volunteer bias. 
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Random Sample

Equal chance, every person in the target population has an equal chance of being selected. HOW? Lottery method. all members of the target population are given a number in a hat or tombola.

Strengths

  • Potentially unbiased.the reseacher has no influence over is selected. free from reseacher bias.

Weaknesses

  • Representation not guaranteed. still possible that a random method may produce a biased sample. limits ability to generalise.
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Sytematic sample

sample frame, ppts are selected using a set pattern. HOW? every nth person is selected from a list of the target population.

Strengths

  • Unbiased. the first item is usually selected at random. objective method.

Weaknesses

  • Time and effort, a complte list of the population is required. may as well use random sampling.
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Stratified sample

Frequency. ppts are selected according to their frequency in the the target population. HOW? Subgroups (or strata) are identified, such as gender or age groups. the relative percentages of the subgroups in the population are reflected in the sample.

Strengths.

  • Representative method, the characteristics of the target population are represented. generalisability more likely than other methods.

Weaknesses

  • Stratification is not perfect. strata cannot reflect all the ways in which people are different. complete representation is not possible.
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Ethical issues &ways of dealing with them

conflict= when a conflict exists between the rights of ppts and the aims of the research. 

BPS code of conduct is a quasi-legal document to protect ppts based on four principles: respect, competence, responsibility and integrity.

Ethics commitees weigh up costs (e.g. potential harm) and benefits (e.g. value of research) before deciding whether a study should go ahead.

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Informed consent

Get permission. ppts should be able to make an informed judgement about whether to take part.

Too much information may affect ppts behaviour so alternative forms of consent are:

  • Presumptive- ask a similar group.
  • Prior general- agree to be deceived.
  • Retrospective- get consent after the study.
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Deception

Mialeading= deliberatly misleading or withholding information so consent is not informed.

At the end of the study, ppts should be given a debrief where they are advised of:

1. The true aims of the investigation.

2. Details that were not given during the study  e.g. existence of other groups or conditions.

3. What their data will be used for

4. Their right to withhold data.

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Protection from harm

Risk= ppts should be at no more risk than they would be in everyday life.

  • Should be given the right to withdraw at each stage of the research process.
  • Should be reassured that their behaviour was typical/normal during the debriefing.
  • Researcher should provide counselling if ppts have been, e.g. distressed
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Privacy/ confidentiality

Right to control= we have the right to control information about ourselves. if this is invaded, confidentiality should be respected.

  • If personal details are held these must be protected (a legal requirment ). usually though, no peersonal details are recorded.
  • Researchers refer to ppts using numbers, initails or false names.
  • Ppts personal data cannot be shared with other researchers. 
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Correlations

Association= Illustrates the strength and direction of an association between two co-varaibles.

ScattergramCorellations are plotted on a scattergram. one co-varaibles is on the X-axix, the other is on the y-axis.

TYPES OF CORRELATIONS:

  • POSITIVE= co-varaibles rise or fall together
  • NEGATIVE= one co-varaibles rises and the other falls
  • ZERO=  no relationship between the two varaibles
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Correlations

Differences between correlations and experiments:

  • In an experiment the researcher manipulates the IV and records the effect on the DV. In a correlation there is no manipulation of variabls and so cause and effect cannot be demonstrated.
  • In a correlation the influence of EVs is not controlled so it may be that a third untested varaible is causing the relationship between the co-varaibles =intervening variable 

Strengths

  • Useful starting point for research. be assessing the stregths and direction of a relationship, correlations provide a precise measure of how two variables are related. if varaibles are strongly related it may suggest hypotheses for future research.
  • Relatively economical. unlike a lab study, there is no need for a controlled environment and no manipulation of varaibles is required. correlations are less time consuming than experiments.

Weaknesses

  • No casue and effect. correlations are often presented as casual, e.g. by the media, when they only show how two varaibles are related. there may be intervening varaibles that explain the relationship.
  • Method used to measure variables may be flawed. e.g., the method used to work out an aggression score might be low in reliability. this would reduce the validity of the correlation study.
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Observation

A way of seeing or listening to what people do without having to ask them. is often used within an experiment as a way of assessing the DV.

Strengths

  • Can capture unexpected behaviour. people often act differently from how they say they will in self-report methods. observations are useful as they give insight into spontaneous behaviour.

Weaknesses

  • Risk of observer bias, researchers interpretation of the situation may be affected by expectations. bias can be reduced using more than one observer.

Naturalistic: takes place where the target beh would normally occur.

Strengths

  • High external validity. in a natural context, beh is likely to be more spontaneous. more generalisble to everyday life.

Weaknesses

  • Low control. there may be uncontrolled EVs. makes it more difficult to detect patterns.
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Obsevations

Controlled= some control/manipualtion of variables including control of EVs.

Strengths

  • Can be replicated, more easily repeated due to standardised procedures. findings can be checked to see if they occur again.

Weaknesses

  • May have low external validity. beh may be contrived as a result of the setting. Findings cannot be applied to everday experience.

 

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observation

Covert= ppts are unaware they are being studied.

+ Demand characteristic reduced, ppts do not know they are being watched so thier beh will be more natural, this increases the validity of the findings.

 

- Ethically questionable. people may not want beh recorded, even in public.ppts right to privacy may be affected

Overt= ppts are aware of being studied.

+ More ethically acceptable. ppts have given their consent to be studied. they have the right to withdraw is they wish.

- Demand chracteristic. knowledge of being studied influences beh. reduces the validity of the findings.

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Observations

Participant= When the research becomes part of the group they are studying.

+ Can lead to greater insight. researcher experience the situation as the ppts do. this enhances the validity of the findings.

- Possible loss of objectivity. the research may identify too strongly with those they are studying. this threatens the objectivity and validdity of the findings.

Non participant= when the researcher remains seperate from the group they are studying.

+ More objective. researcher maintains an objective distance so less chance of bias. may increase the validity of the findings.

- loss of insight. researcher may be too far removed from those they are studying. may reduce the validity of the findings.

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Observatioal design

Behavioural categories= the target beh to be observed should be broken up into a set of observable categories. this is similar to the idea of operationalisation.

- Difficult to make clear and unambiguous, categories should be self- evident and not overlap, not always possible to achieve. smilling and grinning would be poor categories.

- Dustbin categories, all forms of beh should be in the list and not one dustbin, dumped behaviours go unrecorded.

Time sampling= observations are made at regular intervals, e.g. once every 15 seconds.

+ Reduces the number of observations, rather than recording everything that is seen i.e. continuous data is recorded at certain intervals. the observation is more structured and systematic.

- May be unrepresentative. the researcher may miss important details outside of the time-scale. may not reflect the whole beh

Event sampling= a target beh/event is recorded every time it occurs.

+ May record infrequent beh, the researcher will still pick up beh that do not occur at regular intervals, such beh could easily be missed using time sampling

- Complex beh oversimplified, if the event is too complex, important details may go unrecorded. this may affect the validity of the findings.

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Questionnaires

Are made of a pre-set list of written questions to which a ppts responds. can be used as a part of an expe to assess the DV

+ Can be distributed to lots of people, can gather large amounts of data quickly & the researcher need not be present when comppleted, reduces the effort involved & makes questionnaires cost-effective

+ Respondents may be willing to open up. they may share more personal info than in an interview as they are less self-conscious. there may be less chance of social desirability bias compared to an interview.

- Responses may not always be truthful, respondents tend to present themselves in a positive light, thus social desirability bias is still posible.

- Response bias, repondents may favour a particular kind of response ,e.g. they always agree, this means that all respondents tend to reply in a similar way.

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Interviews

Face to face interaction between an interviewer and interviewee.

structured interview= List of pre determined questions asked in a fixed order.

+ Easy to replicate. straightforward to replicate because of standardised format, format also reduces differences between interviewers.

- Interviewees cannot elaborate, interviewees cannot deviate from the topic or elaborate their point. this may be a source of frustration for some.

Unstructured interview= There are no set questions. there is a general topic to be discussed but the interaction is free flowing & the interviewee is encouraged to elaborate.

+ thers is greater flexibility, unlike a structured interview, points can be followed up as they arise, more likely to gain insight into interviewee's worldview.

- Difficult to replicate, such interviews lack structure & are not standardised.> risk on interview bias

semi-structured interviews= list of q.s that have been worked out in advance but inter are free to ask follow up q.s when appropiate

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Design of questionnaires

Writing good questions.

  • Avoid jargon: Do u agree that maternal deprivation in infanthood inevitable leads to affectionaless psychopathy?
  • Avoid double-barrelled q.s: Do u agree that footballers are overpaid and should give 20% of their wages to charity?
  • Avoid leading q.s: Do u agree that boxing is barbaric?
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types of questions

Closed questions= respondents has limited choices. data are quantitative, e.g. How many cigarettes do u smoke a day? 0-10,11-20,21-30,30+

+Easier to analyse. can produce graphs & charts for comparison, makes it easier to draw conclusions.

- Respondents are restricted, forced into an answer that may not be representative of true feelings, may reduce validity of the findings.

Open questions= respondents provide their own answers expressed in words. data are qualitative, e.g. Why did u start smoking?

+ Respondents not restricted, answers more likely to provide detailed, unpredictable info, likely to have more validity than statictics.

- Difficult to analyse, wide variety of answers than produced by quantitative data, may be forced to reduce data to statistics.

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Design of interviews

Interview schedule= A standardised list of q.s that the interviwer needs to cover, can reduce interviewer bias.

Quit room= Will increase the likelhood that the interviewee will open up.

Rapport= Begin with neutral questions to make ppts feel relaxed.

Ethics= Remind interviewees that answers will be treated in confidence.

Pilot studies

  • Used in all types of research
  • a pilot study is a small scale trial run of a research design before doing the real thing.
  • aim of piloting= to find out if certain things don't work so u can correct them before spending time and money on the real thing.
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Types of data

Quantitative data= numerical data, e.g. reaction time or number of mistakes

+ Easier to analyse, can draw graphs and calculate averages, can eyeball data and see patterns at a glance.

- Oversimplifies beh, e.g. using rating scale to express feelings, means that individual are lost.

Qualitative data= non numerical data expressed in words,e.g extract from a diary.

+ Represents complexities, more detail included, e.g. explaining ur feelings, can also include info that is unexpected.

- Less easy to analyse, large amounts of detail is difficult to summarise, difficult to draw conclusions, many ifs and buts.

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Primary and secondary data

Primary data= first hand data collected for the purpose of the investigation.

+ Fits the job, study designed to extract only the data needed, info is directly relevant to research aims.

- Requires time & effort, design may involve planning & preparation. secondary can be accessed within min

Secondary data=  collected by someone other than the person who is conducting the research , e.g. taken from journal  articles, books etc.

+ Inexpensive, the desired info may already exits, requires minimal effort making it inexpensive.

- Quality may be poor, info may be outdated or incomplete, challenges the validity of the conclusions.

Meta analysis=  type of secon data that involves combining data from a large num of studies,

+ Increses validity of conclusions, the eventual sample size is much larger than individual samples, increases the extent to which generalisations can be made.

-Publication bias, researchers may not select all relevant studies, leaving out negative or non-significant results, data may be biased bec it only represent some of the data & incorrect conclusions are drawn.

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Measures of central tendency

Mean= arithmetic average, add up all the scores & divide by the number of scores.

+Sensitive. includes all the scores in the data set within the calculation, more of an overall impression of the average than median or mode.

- May be unrepresentaive. one very large or small num makes it distorted, the median or the mosde tend to be so easily distorted.

Median= middile value, place scores in ascendinf order and select middle value, if there are two values in the middle, the mean of these is calculated.

+Unaffected by extreme scores, the median is only focussed on the middle value, it may be more representative of the data set as a whole.

- Less sensitive than the mean, not all scores are included in the calculations of the median, extreme values may be important.

Mode= most frequent or common value, used with categorical/ nominal data

+Relevant to categorical data, when data is discrete i.e. represented in categories. sometimes the mode is the only appropriate measure.

- an overly simple measure. there may be many modes in a data set. it is not a useful wayof describing data when there are many modes.

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Mesure of dispersion

Range=  the difference between highest to lowest value (+1)

+ Easy to calculate, arrange values in order & subtract from largest from smallest, simple fromula, easier than the standard deviation.

- Does not account for the distribution of the scores, the range does not indicate whether most numbers are closely grouped around the mean or spread out evenly, the standard deciation is a much better measure of dispersion in this respect.

Standard devition= measure of the average spread around the mean, the larger the SD , the more spread out the data are.

+More precise than the range, includes all values within the calculartions, a more accurate picture of the overall distribution of the data set

- it may be misleading, may hide some of the characteristics of the data set, extreme values may not be revealed, unlike with the range.

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