Research methods - Year 1

What variables are used in experiments?

independent variable - factor that changes between conditions which is aspect that has been manipulated by researcher or naturally changes
dependent variable - factor you measure must have a unit + caused by change of IV
all other variables that could affect DV should be controlled so researcher able to confidently conclude that effect on DV was caused only by IV
to test effect of IV need different conditions - experimental condition + control condition where you can have various experimental conditions 

What are aims?

should include a general statement of why research is taking place what is being studied and what the study is trying to achieve
eg - to investigate whether drinking energy drinks makes people more talkative

What is a hypothesis?

testable statement about behaviour that researcher aims to support by use of an objective test and describes behaviour in general not behaviour of participants in the experiment - should be in the present tense and written at start of research process before results are known

What are the two different types of hypothesis?

alternate/experimental hypothesis - will predict a significant difference in dependent variables as a result of manipulation of the independent variable
null hypothesis - will predict no significant difference in dependent variable as a result of manipulation of the independent variable as simply suggests your results could have occured by chance

What direction can hypothesis be?

directional - indicates which way dependent variable will change known as one-tailed test
non-directional - suggests there will be a difference but difference could be either an increase or decrease in DV known as two-tailed test
choice may depend on whether there has been previous research

How to write hypotheses?

include IV (both conditions) and DV (make sure there is a unit of measurement) and operationalise both variables
decide if you want it to be directional or non-directional and use the word significant - don’t talk about participants also people and use present tense

What are some possible frameworks?

directional
people who IV 1st condition score significantly higher on DV than people who IV 2nd condition
non-directional
there is a significant difference in DV between people who IV 1st condition and people IV 2nd condition
null hypothesis
there is no significant difference in DV between people IV 1st condition and people IV 2nd condition or any difference between IV 1st condition and IV 2nd condition when DV is due to chance

How do you write hypotheses when doing a correlational analysis?

there is a significant positive/negative between variable A and variable B (directional)
there is a significant correlation between variable A and variable B (non-directional)
there is no significant correlation between variable A and variable B (null)

What is operationalisation of variables?

act of researcher clearly defining variables in terms of how they are being measured therefore being as specific as possible
variables should be defined and measurable eg DV - words remembered - heart rate - rating on scale - test on score
IV - caffeine consumed - time allowed for rehearsal

What is one way of control of variables/research issues?

extraneous variables - factors other than IV that might affect the DV
identified at start of experiment and steps taken to minimise their influence - some EVs can be controlled easily such as age of participants or lighting in lab but some are harder to control eg personalities + individual motivation levels
confounding variables - EV which have affected your results - makes difficult for researcher to be sure IV has affected the DV
eg - time of day in a memory test as later in day may be tired

control of variables

icnlduing demand characteristics and investigator effects
randomisation

What are the four type of experiments?

laboratory experiments
field experiments
natural experiments
quasi-experiments

What are laboratory experiments and the strengths and limitations?

carried out in a controlled environment + IV is manipulated by researcher
strengths - high levels of control over EVs means researcher can ensure any effect on DV is likely due to manipulation of IV so can be more certain about demonstrating cause and effect (high internal validity) 
replication is easier due to high level of control - ensures new EVs are not introduced + vital to see results are valid and not just a one-off
limitations - low external validity so may lack generalisability as lab environment may not reflect everyday life as so controlled no relation to real life
participants aware being tested in lab and may cause unnatural behaviour known as demand characteristics as may try to guess behaviour
tasks may not represent everyday experience eg recalling unconnected words in a memory experiment which doesn’t reflect how we generally use memory known as low mundane realism

What are field experiments and the strengths and limitations?

carried out in a natural environment + IV is manipulated by the researcher
strengths - higher mundane realism than lab as environment more natural so may produce behaviour that is more valid
improved external validity so able to generalise better + reduces demand characteristics
limitations - less control of EVs means cause and effect between IV and DV in field studies may be more difficult to establish
harder to accurately replicate to check reliability
may be ethical issues if participant unaware being studied and they cannot consent to be studied and such research might be an invasion of privacy

What are natural experiments and the strengths and limitations?

IV is not manipulated by researching it instead changes naturally eg IV might be before and after an earthquake where situation would have changed anyway just effects recorded this can occur in a lab and DV may also be natural eg exam results
strengths - provides opportunities for research in areas where it may be unethical to manipulate IV eg Romanian adoptees
often have high external validity as involves study of real-world issues and problems as they happen
limitations - naturally occurring event may only happen very rarely reducing opportunities for research which may also limit able to generalise to other situations and opportunity to replicate
causal connections are difficult as too many extraneous variables to say IV directly causes DV

What are quasi-experiments and the strengths and limitations?

have IV based on exisiting difference between people eg age or gender meaning participants cannot be randomly allocated to conditions the IV cannot change eg anxiety levels in people with and without phobia were compared and IV of having phobia would not come about through any experimental manipulation other than this can be like any other type of experiment
strengths - allows comparison between different types of people
carried out often under lab conditions and therefore share some strengths of a lab experiment
limitations - cannot randomly allocate participants to conditions so makes extraneous variables likely so therefore causal connections are harder
IV not deliberately changed by researcher and therefore cannot claim IV has caused any observed changes

What is a population and a sample?

population - large group of individuals a researcher is interested in studying often called target population as subset of general population usually not all members so researcher will choose smaller groups called samples - ideally sample will be representative so can generalise findings - larger the sample more likely it will reflect target population as participant variables will be reduced

What is the sampling design 1 and evaluation?

random sample - selected indiscrimantly from group where every member of target population has equal chance of being chosen - complete list of target population is numbered + actual sample chose by lottery method
pros - reduces bias meaning extraneous variables potentially equally divided between different groups enhancing internal validity - sample likely to be representative of target population
cons - sample can still be bias (eg all males) so may not be representative - time-consuming - difficult to obtain complete list of target population

What is the sampling design 2 and evaluation?

systematic sample - every nth member of target population is selected - sampling frame produced which is list of people in target population for instance alphabetical + sample system is selected - may begin at randomly determined point then every nth person
pros - low chance of researcher bias as once system decided researcher has no influence over who is chosen - likely to be quite representative
cons - population needs degree of randomness eg houses along street of similar type wouldn’t represent sample of residents in a borough - if starting point chosen may be degree of bias - participant may refuse to take part resulting in a volunteer sample + thus may result in bias sample

What is the sampling design 3 and evaluation?

startified sample - compisition of sample reflects the proportions of people in certain subgroups (strata) within target population - first identify different strata then proportions needed for sample to be representative are worked - then in each strata participants are chosen randomly from larger population
pros - best chance of being representative as designed to accurately reflect composition of population meaning findings can be generalised more easier - reduced resercher bias
cons - identified stratas cannot reflect all different strata of population so not completely representative - time-consuming - not always easy to get information you need eg household income

What is the sampling design 4 and evaluation?

opportunity sample - using participants who happen to be available + willing to take part eg students in my class or people you stop in street
pros - convienient as more economical in time and money as list of members not required
cons - unrepresentative of target population as drawn from very specific area so findings cannot be generalised to target population - researcher has complete control over selection of participants + may avoid people they don’t like the look of (researcher bias)

What is the sampling method 5 and evaluation?

volunteer sample - using those who respnds to an advert eg a poster in a common room or advert in newspaper
pros - more economical as requires minimal input from researcher so less time-consuming + more engaged than those stopped on street
cons - volunteer bias as asking for volunteers may attract a certain profile of people who are curious and more likely to please researcher + be more helpful than general population therfore behave differently so may not be able to generalise findings

What are the three ways to organise your participants?

repeated measures
independent groups
matched pairs

What is repeated measures and evaluation?

uses the same participants in each condition so each participant does all conditions
pros - participant variables are controlled therfore higher validity
cons - order effect where when both conditions repeated can be affected by fatigue or practise (can be controlled by counterbalancing where half participants do one condition first and the other half does other condition first) - more likely participants will work out aim of study when they experience all conditions increasing demand characterisitcs

What is independent groups and evaluation?

uses different participants for each condition so each participant does one condition - should be randomly allocated to groups
pros - no order effects - reduced chance of demand characteristics since less likely to guess what behaviour expected - only need one set of stimulus
cons - group differences meaning working out mean difference between groups DVs may be more to do with participant variables than effects of IV where these differences may act as extraneous variable reducing validity of findings (larger sample will reduce effect of participant variables)

What are matched pairs and evaluation?

participants are paired together on variables relevant to an experiment eg in a memory study participants may be matched on IQ - done by making participants take some sort of test then pair top two scores and randomly allocate to conditions then repeat
pros - participants only take part in a single condition so order effect reduced
cons - participants can’t be matched exactly which may affect the DV - participants may guess the aim of experiment since IV more noticeable

What are pilot studies?

small-scale trial run on an actual investigation to make sure everything works the way you had planned and allows investigators to identify and correct problems and modify design before main study which saves time and money in the long run
issues could include: unclear instructions - misunderstandings - inaccurate measuring equipment - unclear behavioural categories - stimulus materials that don’t work - time allowed may be too long or too short

single and double blind procedures

What is the main non-experimental methods?

observation provides psychologists seeing what people do without having to ask them giving research flexability to study more complex interactions between variables in a natural way + can be used in experiments for assessing the dependent variable
all observations not possible to establish cause and effect + may suffer from observer bias as their interpretation may be affected by expectations

What settings can observations occur in?

if observation takes place in setting or context where target behaviour would usually occur then called naturalistic observation where all aspects of environment are free to vary
if useful to control certain aspects of research then controlled observation may be preferred where some control over variables including manipulating variables to observe effects and also control of extraneous variables

What is evaluation of naturalistic and controlled observations?

N observation tends to have high external validity so findings can be generalised to everyday life because behaviour is studies in normally occuring environment but as lack of control over research hard to replicate and may also be many uncontrolled extraneous variables
C observation may have fewer extraneous variables and easier to replicate but they produce findings that cannot be as readily applied to real-life settings

What are the different observations of participants?

behaviour recorded without first obtaining consent of participants and are unaware they are the focus of the study then called covert observation which must happen in public in order to be ethical
in contrast overt observations are when participants know their behaviour is being observed and have given their informal consent beforehand

What is the evaluation of covert and overt observation?

in covert participants don’t know they are being watched which removes the problem of demand characteristics and ensure any behaviour observed will be natural increasing internal validity of data gathered however ethics of these studies may be questioned as even in public people may not wish to have their behaviours noted down
overt observations are more ethically acceptable but knowledge participants are being observed may significantly influence their behaviour

How can the researcher be involved in observations?

If observer becomes part of the group they are studying then called participant observations eg factory workers where join group to produce first-hand account
non-participant observations are when researcher remains separate from those they are studying and records behaviour in more objective manner

What is the evaluation of participant and non-participant observations?

in participant observations researcher can experience the situation as the participants do giving them increased insight into lives of people being studied which increases the external validity of the findings however researcher could come to identify too strongly with those they are studying losing objectivity (low internal validity)
where non-participants observations allows the researcher to maintain objective psychological distance from participants giving it high internal validity however may be too far removed from people and behaviour they are studying to gain valuable insight meaning low external validity

What are ways to record observational data?

researcher may simply write down everything they see known as unstructured observation + produces accounts of behaviour which are rich in detail which is more appropriate when it only involves a few participants
however if too much going on in one observation then may need to simplify target behaviour using behavioural categories known as structured observations

What are behavioural categories?

in order to produce a structured record of what a researcher sees they should first break target behaviours up into a set of behaviours categories where target behaviours should be precisely defined ensuring they are observable,measurable and self-evident and therefore should not require further interpretation

What are sampling techniques used in observations?

continuos recording is often not pratical so sampling of observations may be used:
event sampling involves counting the number of times a particular behaviour occurs in target group eg counting number of times players disagree with the referee
time sampling involves recording behaviour at pre-established time intervals eg making note of what target individual is doing every 30 seconds

What is inter-observer reliability?

to make data recording more objective and unbiased observations should be carried out by at least two researchers but it is vital observers are consistent in their judgement and that data they record is similar so must be trained to established inter-observer reliability (data compared to check for consistency) to do this:
observers should familiarise themselves with behavioural categories - observe same behaviour at the same time and observe records of behaviour - observers should compare data they recorded abd discuss any differences in interpretations - finally should analyse data from study and inter-observer reliability is calculated by correlating each pair of observations made and overall figure produced where around 0.8 is considered reliable

What is the evaluation of observational design?

structure makes recording data easier and more systematic and will produce quantitative which makes analysing more straightforward where unstructured has more richness in detail but greater risk of observer bias
behavioural categories should cover all possible forms of target behaviour on checklist and they do not overlap
event sampling useful when behaviour occurs rarely + time sampling effective at reducing the number of observations which have to be made but samples may be unrepresentative of the observation as a whole

more on observational designs

What is correlational analysis?

a mathmatical technique where researcher looks to see if there is a relationship between co-variables where both variables are co-variables which are measured on a continuos scale and is not manipulated
use scattergrams to plot correlations where each pair of values is plotted against each other to see if relationship

What does a positive,negative and no correlation mean?

positive - relationship between two co-variables where as one increases so does the other
negative - relationship between two co-variables where as one increases the other decreases
no - means no relationship exists between variables
when writing hypotheses for correlations used the word relationship null = no significant relationship between
directional=there will be a significant negative/positive relationship between
non-directional=there will be a significant relationship between

What is the correlational co-efficient?

number between -1 and 1 which tells us the strength and direction of the relationship
+ 1.0 perfect positive correlation + 0.8 strong positive correlation + 0.5 moderate positive correlation + 0.3 weak positibe correlation 0 no correlation - 0.3 weak negative correlation - 0.5 moderate negative correlation - 0.8 strong negative correlation - 1.0 perfect negative correlation

What are the differences of correlational studies and experiments?

covariables rather than IV and DV
no manipulation of variables
in correlational causal connections cannot be drawn whilst in experiments this can be inferred
in correlational measurement must be continous scale which doesn’t have to be true in an experiment

What are the pros of correlational analysis?

pros - can suggest areas where future research required as useful preliminary tool for research as by assessing strength of relationship as provide precise and quantifiable measure of how 2 variables are similar which migh suggest idea for possible future experimental research - can study effects of behaviour without manipulation/research variables that would be unethical to manipulate (may be unethical to do so) eg stress and sick days - allows predictions to be made + data collected by others can be used meaning less time-consuming than experiments

What are the cons of correlational analysis?

as lack of control over variables compared to experiments so can only tell us how variables are related but not why + cannot demonstrate cause and effect between variables therefore don’t know which co-variable is causing the other to change so establishing direction of effect an issue
another untested variable may be causing relationship between co-variables known as an intervening variable where certain other factors may be overlooked
due to issues above correlations can be misused or misinterpreted where relationship between variables are sometimes presented as causal when they aren’t especially by the media

What is quantitative data and evaluation?

data that is expressed numerically usually data collection technique usually gather numerical data in form of individual scores such as words recalled - open to being analysed statistically 
pros - relatively simple to analyse as can calculate averages therefore comparisons between groups can be easily drawn + numerical data tends to be more objective + less open to bias 
cons - much narrower in meaning + detail so may fail to represent ‘real life’

What is qualitative data and evaluation?

expressed in words may take form fo written descriptions of thoughts and feelings 
pros - offers a reseatcher more richness of detail so much broader in scope + gives participant opportunity to fully report their thoguhts,feelings + opinions on given subject so tends to have greater external validity as provides researcher with more meaningful insight into participants worldview
cons - difficult to analyse as tends not to lend itself to being summarised statistically so patterns + comparisions within data will be hard to identify - as a consequence conclusions often rely on subjective interpretations of researcher + may be subject to bias particularly if researcher has preconceptions of what expecting to find 

What is primary data and evaluation?

(sometimes called field research) refers to original data that has been collected specifically for the purpose of the investigation by the researcher eg questionnaire,interviews or observations
pros - fits the job (specific) as authentic data obtained from participants themselves for purpose of particular investigation where interviews can be designed in a way that specifically target information researcher requires
cons - requires time and effort as conducting an experiment requires considerable planning,preperation and resources which is a limitation compared to secondary data which can be accessed within a matter of minutes

What is secondary data and evaluation?

data that has been collected by someone other than person conducting research - it already exists before psychologist begins research - known as desk research + often already been subject to statistical testing + significance known eg population records
pros - inexpensive + easily accessed requring minimal effort when researching may find desired information already exists
cons - may be substantial variation in quality + accuracy of secondary data where information may appear valuable but may be out-dated or incomplete as well as data may not match researchers needs 

What is meta-analysis and evaluation?

form of research method that uses secondary data - refers to a process in which data from large number of studies which have involved same research questions + methods of research combined
may simply discuss findings - qualitative analysis or statistical analysis which gives overall statistical measure of relationship between variables across number of studies
pros - allows us to view data with more confidence + results can be generalised across much larger populations
cons - can be prone to publication bias as researcher may leave out studies with negative results meaning will be biased because only represents some of relevant data + incorrect conclusions are drawn

What are the three measure of central tendency pros and cons?

mean - pros - useful when scores cluster around one value + includes all data - cons - extreme scores can give misleading value + cannot be used with nominal data
median - pros - not affected by extreme values + best for ordinal data - cons - not as sensitive as mean since all raw data is not used 
mode - pros - not affected by extreme scores + can make more sense as will be a real score + can be used with nominal data - cons - can be more than one mode so confusing + tells us nothing of other scores

What are the two measures of dispersion pros and cons?

range - pros - easy to calculate - cons - can be disorted by extreme values + tells you nothing about how scores grouped or how many observations are in data set
standard deviation - shows average variation from mean where the lower the score more likely data is tightly clustered around mean implying all participants responded in similar manner 
pros - takes every score into account - cons - harder to calculate - less meaningful if data is not normally distributed and can mask extreme values

What are four ways to present quantative data?

1.contingency tables - used to display data in form of categories
2.bar charts - represent visually difference in mean values - used with discrete data - bars are seperated to denote we are dealing with different categories 
3.histograms - used with continuos data - bars are touching and start at 0 - area of bar represents frequency
4.scattergraph - show association between co-variables - each cross represents one pair of related data + altogether crosses represent strength of correlation - both axes data must be continuos
always clearly label axes + give a title 

What is normal distribution?

meaning most people are located in middle area of curve with few people at extreme ends - mean,median and mode all occupy same mid-point of curve 

What is positive distribution?

positive skew is when distribution is concentrated towards the left of graph + long tail on the right - eg a very difficult test - mode remains at highest point then the median comes next but mean has been dragged across to the right as extreme scores of high-scoring candidates which pull mean to the right

What is negative distribution?

negative skew is when distribution is concentrated towards right of graph + long tail on the left - eg a very easy test - the mean is pulled to the left this time as lower scores are the minority then the median and finally the mode 
all three values are on the longer length of the curve 

What are case studies?

involves detailed study of single individual and is an example of evidence-based research where used to look at unusual behaviours and to look at greater detail - scientific research methods used and aims to use objective and systematic methods where information collected from range of sources such as person and from their family with techniques like being interviewed or observed during daily life could also use IQ or personality tests + may use experimental method to test what target can or can’t do
findings organised into themes to represent individuals thoughts + emotions so may be presented in qualitative way where case studies generally longitudinal following individual or group over extended period of time

What are examples of case studies?

in memory topic HM whose hippocampus was removed resulted in an inability to form new memories + KF whose short-term memory for digits was poor when he heard them but better when he read them
Gage - hit through the skull surviving showing people can live despite loss of large amount of brain matter however did affect personality where case important in brain surgery to remove tumours as showed parts of brain could be removed without fatal effect

What are advantages of case studies?

rich data which other methods may overlook - gets at essence of human experience - can be used to show consequences of rare experiences eg extreme privation as could not ethically create these conditions in experiments - can challenge exisiting theory and lead to new developments or provide evidence that disproves exisiting theory improving knowledge

What are disadvantages of case studies?

difficult to generalise (not usually the point) - recollection can become distorted either by memory issues or way relationship developed with researcher leading to emotions being expressed in way that wasn’t accurate - research bias which occurs in selection of material or in way some issues are explored - ethical issues such as confidentiality and protection of participants can be hard to maintain and may be so many unusual details that people become identifiable

What are the three levels of measurement?

nominal data - ordinal data - interval data

What is nominal data?

simplest thing a number can do where just a headcount or tally of categories + just tells us how many where you can count discrete data
can count but can’t order data - usually use a code eg male=1 female=0 - occurs in frequencies

What is ordinal data?

allows us to put things in order eg A might be higher than B but lower than C however can’t be sure difference between C and A is the same as difference between A and B so can’t tell the intervals are the same
data can be ordered/ranked - can count and order data eg house numbers or place in race - scale of 1 (dislike) to 5 (like)

What is interval data?

allows us to put things in order just as ordinal but this time can be sure the intervals are the same where we know the difference between 10cm + 15cm is same as 15cm + 20cm where same applies to weight,mass,temperature or time where data usually requires measuring instruments
based on numerical scales eg time + temperature - units of equal measure (scale with equal intervals) are used eg minutes + percentage scores in exam - more precise

What is the sign test?

test can be used to test significance in paired or related (repeated measures or matched pairs)
1 state the hypothesis - 2 for each pair of data add sign + or - depending on which item in pair greater + if no difference leave blank - 3 find calculated value of test statistic S which is the frequency of less frequent sign - 4 find critical value of S from table of critical values where N=total number of scores (ignoring blank rows) and choosing one or two tailed test and level of significance of P less than 0.05 or 0.01 - 5 compare calculated value with critical value following instructions below table to see if difference is significant then decide whether result is in expected direction do whether hypothesis can be accepted

Why do we use the sign test?

to determine whether difference found is significant where to use sign test:
we need to be looking for difference rather than association - we need to have used a repeated measures design - we need data that can be organised into categories known as nominal data where data can be converted into nominal by tallying it

What is the critical value?

when statistical test left with calculated value which needs to be compared with critical value to decide whether result is significant or not
need the significant level desired - number of participants in investigation N value - whether hypothesis is directional (one-tailed) or non-directional (two-tailed)
for sign tests calculated value has to be equal or lower than crictival value for result to be regarded as significant

What is significance?

all results obtained by statistical methods suffer from disadvantage might been caused by pure statistical accident
where level of significance (P) is determined by probability that this has not happened + P is an estimate of probability result has occurred by statistical accident where a significance level frequently quoted as p is less than 0.05 means 5% probality whole thing was accidental
a high value of P represents a low level of statistics significance and vice versa

What is a type 1 error?

make this error when we believe we have found significant result when we haven’t often called false positve where we reject null hypothesis when we should have retained it
type 1 errors often occur when we have set too lenient level of significance if P is more than 0.1 (10% significance)

What is a type 2 error?

make this error when we believe we have found nothing of significance when we actually have often called false negative where we reject alternative hypothesis when we should have accepted it
type 2 errors often occur when we have set too strict level of significance if P is less than 0.01 (1% significance)

What are seven ethical issues in research?

main 5 - informed consent - deception - protection from harm - invasion of privacy - confidentiality
other 2 - conduct - right to withdrew

What is informed consent,why is it an issue and how to deal with it?

participants should have all information needed to make decision so can make an informed judgement on whether or not to take part
should be issued with a consent form detailing all relevant information of what they will have to do (don’t need to say why as could change behaviour) - consent for children under 16 should be sought from parents but this doesn’t give right to data

What is deception,why is it an issue and how to deal with it?

means deliberately misleading or hiding information from participants where they have right to assume won’t be misled into doing anything that might be damaging to them + should only be used when absolutely necessary to prevent changes in behaviour
follow BPS code of conduct + seek consent from ethical comittees - not possible to explain everything then prior general consent (would consent to similar scenarios) + presumptive consent (if other similar participants wouldn’t have minded can presume participants would too) - told what data can be used for and have the right to withold data if they wish

What is protection from harm,why is it an issue and how to deal with it?

participants should not be placed at any more risk than their daily lives + should be protected from physical and psychological harm where they have the right to expect to not be harmed
follow BPS code of conduct - make sure made aware of their right to withdraw - should be reassured behaviour was typical and follow-up if necessary

What is invasion of privacy,why is it an issue and how to deal with it?

participants have the right to privacy + researchers don’t have authority to pry into private lives without permission + extends to area you work at - can only be observed without their knowledge in public places
follow BPS code of conduct - agree guidelines with participants before study commences as part of consent process

What is confidentiality,why is it an issue and how to deal with it?

people have right to remain anonymous + personal data should be protected once privacy has been invaded
remove all personally identifiying information from participants data - refer to participants as numbers or initials to maintain anonymity

What is conduct,why is it an issue and how to deal with it?

people have right to expect appropriately trained researchers are carrying out study + otherwise research could cause harm
ensure researchers have appropriate qualifications and training - follow BPS code of conduct

What is right to withdraw,why is it an issue and how to deal with it?

people cannot be coerced into taking part in research + this right helps people protect themselves
ensure participants are aware they can stop at any time + remand them during procedure - have right to withdraw data up to point of publication + must consider how children may display desire to stop

What is the BPS code of conduct?

British Psychological Society has a code of ethics where researchers have duty to observe these guidelines when conducting research where guidelines attempt to ensure all participants are treated with respect during each phase of research - where use cost-benefit approach to determine whether particular research proposals are ethically acceptable

What are the two self-report techniques?

questionaires - set of written questions that participants fill in themselves
interviews - asking a participants questions
self-report involves asking a participant about their thoughts and behaviour and recording their answers

What are questionaires and what is involved?

usually concerned with opinions and attitudes + can use closed or open questions to collect data which is appropriate to your study
closed questions - choose from limited range of options so will be easy to quantify but can be artificial and lose detail
open questions - participants answer in their own words and will provide rich experiental data about human experience but are time consumong and difficult to analyse

What type of closed questions can be asked?

fixed choice questions are phrased so participant has fixed answers
checklist questions which gives a list of options
ranking questions where put list of options into order
likert scale questions where participant indicates on scale how much they agree
rating scale question where must highlight on numerical scale what reflects their views

What is evaluation of closed questions?

pros - quick and easy for participants to answer - more likely to be structured in certain order so high in internal reliabilty - large samples can be collected increasing generalisability - quantitative data easy to analyse eg find medians and draw graphs
cons - lacks details as participants can’t express opinions fully - risk of response bias (saying yes to everything) - score for all participants on each question is nominal data so only mode can be calculated

What is evaluation of open questions?

pros - produce qualitative data giving participants opportunity to fully express opinions increasing validity - all info analysed so information not lost by averaging answers increasing validity
cons - qualitative data is time consuming to analyse as themes need to be identified - interpretation of data is subjective leading to bias meaning validity issues occur + inconsistency of interpreting data can lead to low inter-rater reliability - findings based on individuals so may lack generalisbility

What are the three types of interviews?

structured interviews - questions are fixed and interviewer reads them out and records responses
semi-structured interviews - have some predetermined questions but interviewer can develop in response to answers given by participants
unstructured interviews - no fixed questions just general aims and is more like a conversation

What is specific evaluation for each interview type?

structured - interview caan be easily be repeated to increase internal reliability - limited by fixed questions + harder to build rapport so might not get high quality information
semi-structured - can respond more flexibly so gain more detailed information - difficult to assess for reliability as questions asked can alter + difficult to repeat exactly as question alter
unstructured - high level rapport so easier to gain knowledge - requires highly trained interviwer + participants may be affected by biases such as social desirability + has low internal validity

evaluation of all

How can validity and reliability be improved for self-report techniques?

validity - removing leading/unclear/poorly operationalised/socially desirable/recall questions/emotive language/double-barrelled questions (can find which ones these are using a pilot study)
adding open questions with qualitative data + adding closed questions to allow for easy quantitative data collection
add filter questions unrelated to study so that participants don’t figure out the aim and display demand characteristics
ensuring answers will be anonymous and confident
reliability - training interviewers so they are standardised - providing standardised questions - adding closed questions with quantifiable data - using split test/test-retest methods

What are factors to consider when choosing between questionaires and interviews?

sample size - social desirability bias (change our answers to be judged favourably) - type of data/depth - flexibility - ethics - sensitivity - ambiguity and interview effects (need to do definitions)

How would you design a questionnaire?

could involve open and closed questions where closed questions could be split into:
likert scale indicates their agreement with statement usually 5 points strongly agree to strongly disagree - rating scale involves having to identify a value that represents their strength of feelings about particular topic - fixed-choice option includes a list of possible options

How would you design an interview?

most involve an interviewing schedule which is list of questions person intends to cover where should be standardised to reduce interviewing bias - interview should be done in a quiet room and away from people increasing openess of answers and its good to start with neutral questions making interviewee feel comfortable and to build rapport where should be reminded answers will be treated in strict confidence

How to write good questions?

if respondants are confused will lead to reduced quality of answers recieved so common errors that should be avoided:
avoid overuse of jargon - which are technical terms only familiar with specialists
avoid emotive language and leading questions - researchers attitude to question may be obvious so emotive language should be replaced by neutral language and leading questions guide to a particular answer
avoid double-barrelled and double negative questions - where respondants may agree with half of the question + double negatives eg not unhappy can be difficult to decipher

What is reliability?

whether your results are consistent or trustworthy where in a case study whether it is replicable
questions to ask include: Would you get the same results if you repeat the tesy in similar conditions? + Are your measurement tools accurate and consistent?

How can reliability be measured?

test-retest method - repeating the same test at a different time and see if you get the sam results of the original test at different time and see if you get the same results of original test
split-half test - ask the same question twice but second question worded differently and results can be correlated using Spearmans where if correlational co-efficient should be above 0.8
alternate test - testing the same aspect by a different method/test

How can reliability be improved?

when possible take more than one measurement for each participant - use a pliot study - standardise way in which researchers collect data (inter-observer reliability) - check data very carefully

What is the first type of reliability and how it can be measured and assessed?

internal reliability which assesses consistency of results across items within a test
split half method - measures extent to which all parts of the test contribute equally to what is being measured - involves asking same question twice but second question worded differently and results can be correlated where strength must be assessed using spearman or pearson where should be above 0.8 to be judged as reliable

What is the second type of reliability and how it can be measured and assessed?

external reliability which refers to extent to which a measure varies from one use ie measures consistency over time and across different situations ensuring it produces similar results

how to improve reability in other aspects eg observations