research methods

Question 1

what are the types of data?

Answer 1

• quantitative
• qualitative
• primary
• secondary

Question 2

quantitative data what is it?

Answer 2

• data in forms of numbers
• can be transformed to tables, graphs, fractions, charts etc
• can be statistically analysed e.g. mean, mode etc

Question 3

quantitative data strengths?

Answer 3

• reliable as easy to compare + analyse as techniques used to collect it are normally replicable
• highlights trends + patterns= useful to apply general laws
• objective, open to bias

Question 4

quantitative data limitations?

Answer 4

• reveals what not why behind a behaviour (lacks explanatory power)
• oversimplify complex things e.g. human behaviours

Question 5

qualitative data what is it?

Answer 5

in forms of words/images e.g. thoughts, feelings etc
- can be analysed using content analysis/thematic analysis

Question 6

qualitative data strengths?

Answer 6

• gain insights into nature of individual experience + meaning
• can expand + deepen knowledge of complex behaviours

Question 7

qualitative data limitations?

Answer 7

• tends to use small sample sizes, difficult to generalise
• subjective= lacks control, hard to analyse + is left to interpretation

Question 8

primary data what is it?

Answer 8

• collected at the source + has not ben previously published
• refers specifically to research aim
• obtained first-hand from the researcher

Question 9

primary data strengths?

Answer 9

• may be more reliable + valid as researcher has full control over data collected
• more trustworthy than secondary data as researcher knows research will be subjected to peer review which if negative could harm reputation
• more specific to research

Question 10

primary data limitations?

Answer 10

• derived from single study compared to secondary data
• expensive, time-consuming

Question 11

secondary data what is it?

Answer 11

• consists of any research findings/results which are pre-existing –> not collected at source/original data collected by other researchers
• has been previously published
• derived from multiple sources e.g. meta-analysis consists of quantitative findings from a range of research studies on same topic

Question 12

secondary data strengths?

Answer 12

• research studies have already been peer-reviewed –> time + money isn’t wasted + researcher can have confidence in data
• provides new insight into existing theories

Question 13

secondary data limitations?

Answer 13

• secondary data may not directly address aim on topic of research –> may be misinterpretation
• unaware of control of original research

Question 14

meta analysis what is it?

Answer 14

• quantitative research method that takes data from published studies (secondary data)
• data from lots of studies that use same technique + research questions are combined
• statistical analysis is performed on results of these studies to produce a effect size as dependent variable to assess overall trends

Question 15

meta analysis strengths?

Answer 15

• less chance of bias results due to secondary data –> researchers can’t influence results= reliability increases as involves lots of studies
• can generalise findings to population due to large amounts of studies included

Question 16

meta analysis limitations?

Answer 16

• secondary data= may not be precise etc
• may be difficult to + time consuming to access relevant studies

Question 17

case studies what is it?

Answer 17

• detailed, in-depth investigations of small group/individual
• allow researchers to examine individuals who have undergone unique/rare experience/are unusual etc
  e.g. someone in a cult/wild boy of Averyon
• collects qualitative (interviews, open questions, questionnaires etc) more subjective individual, personal experience. quantitative data (memory tests, closed questions etc)
• uses triangulation (sometimes involves more than one researcher collecting/analysing data in same study
• tend to be longitudinal (person experience tracked + measured over time)

Question 18

case studies strengths?

Answer 18

• provide rich, in-depth data= high in explanatory power –> whole individual is considered
• conducting case study on unusual person with rare condition= researcher can form conclusions as to how majority of population function
• gains unique insights which would normally be over looked with manipulation of only one variable
• can be used in circumstances that wouldn’t be ethical

Question 19

case studies limitations?

Answer 19

• findings only represent small group/individual= hard to generalise
• if researcher becomes close to person they’re studying= they lose objectivity + may become bias in reporting
• subjective + sometimes unscientific= less validity

Question 20

correlations what are they?

Answer 20

• analysis of relationship between co-variables
• correlation research- variables aren’t manipulated (no IV), instead 2 co-variables are measured + compared to look for a relationship
• correlation uses 2 scores
• case of self-reported data= there are 2 scores per participant
• case of pre-existing data, researcher would go by records
• each ppt. has 2 scores + researcher then calculates to look for a relationship
• score for correlations= plotted on scattergraphs/grams

analyse relationship between co-variables –> eyeball scattergraph to see direction of correlation
-calculate correlation co-efficient which represents strength of relationship between co-variables expressed as value between -1 and +1
- perfect positive correlation= +1
- perfect negative correlation= -1
- no relationship= 0

Question 21

types of correlations?

Answer 21

positive correlation (as one co-variable increases the other one increases)
negative correlation (as one co-variable increases the other decreases)
no correlation (no relationship)

Question 22

correlations strengths?

Answer 22

• data may be easily available for researcher to quickly analyse –> enables researcher to access large amounts of data which would otherwise be impossible to gather –> increases reliability
• correlations allow researchers to make predictions as to relationship between 2 co-variables

Question 23

correlations limitations?

Answer 23

• extraneous factors connected to co-variables may affect results -> invalid conclusions
• only work well for linear relationships (height + shoe size), not non-linear (hours worked + level of happiness)= limits type of data that can be analysed

Question 24

nominal data

Answer 24

• used when data put into categories/groups provides little info or insight e.g. attachment type
• discrete data- can only appear in one category

Question 25

ordinal data

Answer 25

- data placed in some kind of order or scale e.g. most to least aggressive

Question 26

interval data

Answer 26

- data measured in fixed units with equal distance between points on the scale --> equal intervals between each value e.g. number of correct answers, numerical scales (temperature) - intervals are equal in size

Question 27

presentation of data- graphs/tables

Answer 27

- don't contain raw scores (e.g. individual scores on a test) of the data --> instead they're converted to descriptive statistics to present overview of results e.g. mean + standard deviation - clear, straight forward at summing up results per condition

Question 28

presentation of data- bar charts

Answer 28

- used when data is divided into categories (discrete data) values in set are distinct + separate - bar charts have gaps between each category --> x-axis shows category/condition --> y-axis shows score/percentage

Question 29

presentation of data- histogram

Answer 29

- display continuous data (have finite/infinite interval e.g. 3.265 vs discrete which would be 3 - don't have gaps between bars - x-axis represents categories - y-axis represents frequencies of the categories

Question 30

presentation of data- scattergrams

Answer 30

used for correlations

Question 31

presentation of data- line graph

Answer 31

represents continuous data

Question 32

presentation of data- distributions (normal distribution)

Answer 32

- spread of data around the mean - symmetrical around the mean - tails never touch x-axis - bell curve - mean, median, mode= all occupy at midpoint of curve, they all have similar values - left of peak= ppl that score less than mean + right= ppl that score more

Question 33

presentation of data- distributions (skewed distributions)

Answer 33

- behaviours/test scores don't always fit into normal distribution so skewed distribution is necessary - one tail is longer than the other - data is not distributes evenly positive skew - most values= found on left so long tail on the right - e.g. a hard maths test --> most ppl score low marks + only a few score high (right side of tail) - mode then median then mean negative skew - most values= found to the right= long tail on the left e.g. easy maths test --> most ppl score high , few score low - mean then median then mode

Question 34

mathematical content

Answer 34

- percentages - decimals + decimal places - fractions - ratios - significant figures - standard form - mathematical symbols

Question 35

measures of central tendency + dispersion

Answer 35

- central tendency- any measure of avg value in a set of data mean, median, mode - dispersion- calculate spread of scores range, standard deviation standard deviation --> calculates how much a set of scores deviates from the mean - provides insight on how clustered/spread out scores are

Question 36

statistical testing

Answer 36

- used to determine whether hypotheses should be accepted or rejected --> find out if differences/relationships between variables are significant or just occurred by chance critical value --> in sign test values need to be equal to/lower than it in order to be significant

Question 37

peer review- what is it?

Answer 37

- process of assessing scientific work to decide whether it is worthy of publication in an academic journal --> collections of studies about similar topics --> how science gets communicate therefore important work enters journal in good science --> to decide this it goes through a peer review

Question 38

peer review- how it's done

Answer 38

- once scientist writes up their study it's sent to 2/3 ppl in same field --> these peers review quality + decide whether it's good enough to be seen by scientific community e.g. was it valid, were IV + DV operationalised, were there flaws in design, was analysis appropriate, ensure no plagiarism etc --> peers then comment on work + return it, corrections by original scientist must then be made if needed --> reviewers are normally anonymous

Question 39

peer review- why peer review?

Answer 39

- ensure quality of research is published --> validity of current scientific knowledge is maintained - universities= rated according to quality of research they produce. better quality= more funding for future projects - guards research/data from being fraudulent

Question 40

peer review- evaluation

Answer 40

- anonymity- allows viewers to be honest BUT in small fields some may just use it to critique rivals - publication bias- journal editors feel pressure to publish finding that find positive results --> means negative results which are just as important aren't published as much - reviewer may prevent publication of a rival then repeat study + claim it as theirs --> may only publish research that holds different view to their own --> limiting this publishing= slows scientific progression

Question 41

implications of psychological research and the economy

Answer 41

- economy= system that enables scarce resources to be distributed according to needs + wants --> economic implication= effect that something eg. research finding may have on this - research in psychology can have ripple effects in society e.g. cause social change, adopt new ideas How governments spend money= has implications in economy - health, education, leisure, law + order, depression - economic implications on small scale= how individual is impacted --> women who take maternity leave= perceived as less reliable by employers= overlooked for promotions - research shows a happy workforce= more productive --> means schemes to boost staff well-beings may be introduced - ppl that work= contribute more to economy through taxation

Question 42

what are components of psychological research?

Answer 42

- psychological research has between 2000-9000 words - abstract, introduction, methods, results, discussion, conclusion, limitations

Question 43

components of psychological research- abstract + introduction

Answer 43

- abstract= 200 words, brief overview of paper - introduction= sets the scene, lays out the aims, reviews current literature

Question 44

components of psychological research- methods + results

Answer 44

- methods- how the research is conducted, who the ppts were, how did we collect the data (interviews, case studies etc), analyse of data (correlations, standard deviation) - results- (can be together or apart from discussion), presents results collected in format that's accessible, identifies patterns/trends/relationships

Question 45

components of psychological research- discussion + conclusion + limitations

Answer 45

- discussion- critically evaluate/analyse data, discuss reasons/impacts of results with ref to earlier research - conclusion- summarise findings + propose anything that might happen in the future (further development) - limitations- outline limitations of research, generalisability, validity, reliability etc

Question 46

what makes a subject scientific?

Answer 46

- paradigm + paradigm shifts - role of theory - falsification - role of peer review - role of hypotheses testing - use of empirical methods - replication - generalisation

Question 47

what makes a subject scientific- paradigm + paradigm shifts

Answer 47

- brings together all assumptions that scientists are prepared to accept about: 1. what they're studying 2. how they'll think about it 3. how they will study it - majority of researchers with subject must agree with work + work within this common paradigm (like a set of universal laws from which theories are constructed) - paradigm shifts occur when there's too much contradictory evidence to ignore -> many researchers question the accepted paradigm e.g. shift from Newton's law to Einstein or shift from smoking - paradigm= basic assumptions, ways of thinking etc accepted by grps/members

Question 48

what makes a subject scientific- role of theory

Answer 48

- theory= explains observable behaviours + events using a set of general principles. It can be used to predict observations theories role: 1- give purpose + direction to research by organising facts + patterns into a set of general principles 2- theories therefore generate testable hypotheses which offer testable predictions of the facts organised by the theory

Question 49

what makes a subject scientific- falsification

Answer 49

- karl popper- suggested psychologists should hold themselves up for hypotheses testing + possibility of being proven false --> even if scientific principle has been proven true repeatedly it may not be the case - theories that survive the most attempts to falsify= the strongest (not because they're definitely true but because they haven't been proved wrong - for theory to be scientific it must be open to falsification

Question 50

what makes a subject scientific- role of peer review

Answer 50

- essential to check quality, relevance, honesty, validity of research

Question 51

what makes a subject scientific- role of hypothesis testing

Answer 51

- allows researcher to refute or support theory --> done in a controlled way altering only one variable at a time --> degree of support for hypothesis determines degree of confidence in a theory

Question 52

what makes a subject scientific- the use of empirical methods

Answer 52

- use careful observations + experiments to gather facts + evidence - variables highly controlled + objectively measured= cause-effect relationships can be found e.g lab experiments, empirical methods use standardised procedures= more replicable

Question 53

what makes a subject scientific- replication

Answer 53

- repeating experiment (same method) to see if same results can be achieved --> increases confidence in validity of results so they can be built upon, strengthens theory through attempts of falsification --> something discovered that can't be replicated= not accepted

Question 54

what makes a subject scientific- generalisation

Answer 54

- sample should be large enough + representative to apply to other situations/wider population - should be possible if findings are objective + appropriate research methods has been used

Question 55

sampling methods

Answer 55

- start of research, researcher must identify target population --> sample used in research = taken from target population + presumed to be more representative of the population (higher generalisability) --> population (large group of ppl who researcher may be interested in studying) , sub group of general population (see diagram on mind map) opportunity volunteer stratified systematic random

Question 56

sampling methods- opportunity

Answer 56

opportunity - researcherobtaining sample from those who are present + available at the time + willing to take part in research S: - convenient, quick, easy way of obtaining ppts (who will all be willing) L: - can't generalise findings as only represent a small group of ppl - researcher bias when choosing ppl to approach

Question 57

sampling methods- volunteer

Answer 57

- people actively selecting themselves to participate in study (self-selecting) - may see posters, media, newspapers etc + choose to take part --> advertising research, advert may ask for specific characteristics e.g. ADHD S: - quick, easy, cost-effective - ppl more willing + enthusiastic= better results L: - volunteer bias --> results hard to generalise (often volunteers have similar personality traits e.g. outgoing) - volunteers= eager to please= demand characteristics

Question 58

sampling methods- stratified

Answer 58

- generates small scale reproduction of target population (they're divided + categorised according to key characteristics required by research to be representative S: - representative of target pop as based on exact proportions= easy to generalise data - researcher has control over categories which can be selected according to how relevant they're to the aim L: - can't confidently classify every member of public to sub-group (not always perfect) - can be time-consuming

Question 59

sampling methods- systematic

Answer 59

- selecting every nth person from a list to make a sample e.g. every 10th person etc S: - unbias as researcher has no control= more representative +generalisable, quick, easy, cost-effective L: - technique= not completely bias free - no guarantee it'll be representative

Question 60

sampling methods- random

Answer 60

- least bias - all ppts have equal chance of being selected - uses names out of hat, random number generator etc S: - eliminated researcher bias as they have no control on who's selected - findings should be fairly representative + generalisable L: - time-consuming + impractical - sample can be non-representative (no guarantee it's always going to be representative)

Question 61

aim

Answer 61

general statement covering topic that will be investigated --> straightforward of what researcher will attempt to find out by conducting investigation - identifies purpose of the research

Question 62

hypotheses

Answer 62

- a testable statement written as a prediction of what the researcher expects to find as a result of experiment - precise + unambiguous

Question 63

experimental hypotheses/alternative hypotheses

Answer 63

- includes IV + DV --> both should be operationalised which involves specifics on how each variable is manipulated + measured e.g. will state students recall more info on a Monday morning than a Friday afternoon

Question 64

what are the types of experimental hypotheses

Answer 64

- Directional/one tailed predicts direction of the difference in conditions i.e. one condition will out-perform the other 'women are significantly better drivers than men' --> one tailed, it states the direction the results are expected to go (one group will do better than the other) - non-directional/two-tailed doesn't predict direction of difference in conditions i.e. it just predicts a difference that will be shown e.g. 'anxiety influences performance'

Question 65

null hypotheses

Answer 65

- begins with an idea that IV will not affect the DV e.g. no difference on amount recalled on a monday morning vs friday afternoon --> only difference due to extraneous/confounding variables - hypotheses for correlation investigations written in same way as experimental ones BUT instead of using the term 'difference' it will use 'relationship/correlation' e.g. there will be a relationship between

Question 66

variables

Answer 66

independent dependent extraneous variables confounding variables

Question 67

independent + dependent variables

Answer 67

independent - only variable changed/manipulated in an experiment - required to observe the effect it has on DV which is being measured dependent - variable that is being measured to determine the outcome of the experiment/assess the affect of the IV

Question 68

operationalising IV + DV

Answer 68

operationalising IV + DV- refers to how both the IV + DV are implemented by a researcher (need to be CLEAR)- defining variables - operationalising IV- researcher needs to set up + define each condition= it's clear difference between conditions being investigated - operationalising DV- researcher needs to design a procedure which enables relevant + appropriate data to be collected with no ambiguity involved

Question 69

extraneous + confounding variables

Answer 69

extraneous - factors that may affect the DV (e.g. time of day, mood, temp etc) - usually controlled so they have same effect across all conditions - removig extraneous variables= research is objective + unbiased - if extraneous variables aren't controlled they become confounding variables - confounding variables can affect DV + negatively impact research findings, so if they occur they need to be acknowledged in 'discussion' section in psychological report

Question 70

single blind + double blind procedures

Answer 70

single blind procedure- ppts not told any info on procedure until end of study to control for demand characteristics double blind procedure- neither ppts of researcher are aware on aims in investigation= reduces investigator effects

Question 71

experimental design

Answer 71

- how participants are allocated to different conditions in an experiment - random allocation used to decide which condition --> ensures wide spread, unbias results independent groups repeated measures matched pairs

Question 72

experimental design- independent groups

Answer 72

- participants only experience one condition of the IV - generates unrelated data (each group generates its own data) - participants= randomly allocated to each condition of the IV (avoid bias) S: - demand characteristics unlikely to be a confounding variable - order effects= less of a problem as only involves one condition --> less likely to become tired= increase validity L: - more ppts needed for design - ppt variables (characteristics etc) = affect validity

Question 73

experimental design- repeated measures

Answer 73

- ppts experience all conditions of the IV - generates related data (scores between conditions for ppts are compared) - ppts= own control group S: - participant variables (sex, culture, mood etc)= not an issue - fewer ppts needed L: - demand characteristics can become confounding as ppt more likely to guess the aim of study + act accordingly - order effects can lower validity due to boredom of tasks

Question 74

experimental design- matched pairs

Answer 74

- where ppts are matched based on specific characteristics e.g. age, IQ etc - matching ppts across conditions= one condition doesn't compromise over-representation - matched pairs= randomly allocated to one condition each S: - limits individual differences as confounding variable as each ppt performance= compared to someone similar to them --> ppt variables controlled - demand characteristics reduced (ppt= only takes part in 1 conditioning of IV) L: - matching=difficult + time-consuming - impossible to match ppts across all criteria (lowers reliability) - if one ppt drops out of research= need to find a replacement

Question 75

demand characteristics

Answer 75

when a ppt acts in a way to meet requirements they assume assessor wants --> controlled with single-blind procedure

Question 76

order effects + how are they reduced

Answer 76

- difference in responses of a ppt due to order of presentation of a task - ppt may become bored, tired ec reduce order effects with COUNTERBALANCING - where order of diff conditions is diff for all ppts e.g. 20 ppl do condition of A then B and 20 ppl do condition of B then A

Question 77

investigator effects

Answer 77

- any effect of investigators behaviour on outcome of study e.g. design of study/interaction with ppts/order of experimental conditions etc

Question 78

standardisation + randomisation

Answer 78

standardisation- using exactly same procedures + instructions for all ppts in research randomisation- use of chance methods to control effects of bias when designing + planning experiment

Question 79

pilot studies

Answer 79

- small-scale trials that are run to test some/all aspects of an investigation --> basically a 'dress rehearsal' of the procedure conducted b4 research to identify any issues which could arise - enables researcher to identify any problems + fix them to suitable alternatives - identify if it's worth time, money + effort to run the experiment

Question 80

types of experiments

Answer 80

- laboratory - field - quasi - natural

Question 81

laboratory experiment

Answer 81

- research methods where researcher has high control over environmental factors/what happens in process etc --> effects of IV + DV can be observed + measured - uses standardised procedures= ensures replicability + reliability - only the IV changes, everything else constant --> means DV can be measured exactly with quantitative data S: - easy to establish cause-effect relationships between IV + DV --> high internal validity due to control + objective nature - use standardised procedures= replicable + reliable W: - lacks ecological validity due to artificial task --> hard to generalise - demand characteristics- limits generalisability of findings --> ppt knows they're in a study= alter behaviour --> lower external validity

Question 82

field experiment

Answer 82

- research method in a natural setting (not lab) - researcher has less control due to real world location --> so many extraneous variables - still involve IV + DV - collect quantitative data (can collect qualitative as well to comment on quantitative findings etc) S: - artificiality reduced- high external validity as experimented more likely to act normally - ppts= less likely to experience demand characteristics L: - extraneous variables= more likely to interfere with findings= decrease reliability - difficult to replicate = low reliability

Question 83

natural experiment

Answer 83

- consist in naturally occurring phenoma (researcher can't manipulate IV) - takes place in natural setting + natural changes are observed + measured - IV= naturally occuring - may be conducted in real world settings - may collect qualitative data S: - allows researcher to investigate topics which would otherwise be unethical to study in lab e.g. menta illness etc --> ethical validity - high ecological validity--> has mundane realism + no control L: - causal relationships= hard to determine due to array of variables + no control--> reduce reliability - may have bias= lowers validity --> sample bias, confirmation bias, social desirability bias

Question 84

quasi experiment

Answer 84

- doesn't manipulate IV, uses naturally occurring phenoma - researcher has less control over experimental process as can't randomly allocate ppts to a condition - collects quantitative data as can be run in same way a lab experiment (just the IV can't be controlled by researcher) - diff. to natural experiment as DV can be measured in a lab S: - little manipulation of IV= results have higher external validity - experiment follow a true experimental design= can be replicated with ppts that match original sample demographics (age etc) L: - ppts can't be randomly allocated to condition= ppt variables= hard to determine causality - lack internal validity as other factors may explain the results

Question 85

ethical issues

Answer 85

- ethical considerations put in place to protect ppt and researcher - BPS- publishes code of conduct that all psychologists must adhere to in order for their research to be approved by a funding body + maintain professional reputation

Question 86

ethical issues - informed consent + right to withdraw

Answer 86

informed consent: - ppts should be given detailed info. about what they will be required to do= they can make informed decision about taking part in research - 16 + younger need parental consent - ppl on drugs/alcohol can't give informed consent right to withdraw: - ppts should be made aware that they have the right to withdraw at any time in research --> even after research they can be withdraw + data collected is destroyed + any personal details

Question 87

ethical issues- deception + protection from harm

Answer 87

deception - when ppts are informed of a false aim/task when researcher introduces fake elements to procedure - deliberately misleading/withholding info - may be necessary for validity of the aim --> in this scenario informed consent can't be given but it still needs to be in place protection from harm -ppts must be protected from harm b4 + after experiment - harm (physical, psychological, emotional damage) inflicted on ppt during research - way to protect ppt= ensure they've given full consent + are aware of their right to withdraw - debrief at end of study -researcher should provide counselling if required

Question 88

ethical issues- privacy + confidentiality

Answer 88

- privacy= any invasion of individuals private space/ env which go beyond boundaries of being acceptable - keep individuals so they aren't personally identifiable - confidentiality- ppts should not be disclosed/available to anyone outside research - confidential data can't be traced back to ppt - published research must have non info on who ppts were - ppts may be referred to as numbers (not names) - in debrief ppts= reassured on confidentiality

Question 89

observations (techniques)

Answer 89

- observation= non-experimental method --> involves observing + recording behaviours --> happens in a natural or controlled setting - observers can only investigate observable behaviours --> can't infer motive, intention, feeling or thought from an observation --> can only record a behaviour then link to topic of investigation with no assumption of cause-effect

Question 90

naturalistic observations (techniques)

Answer 90

- one where researcher observes + records behaviours in a natural setting (away from lab) with no manipulation/complete absence of IV - used when it would be inappropriate to run an experiment to investigate topic - ppts may be unaware they're being observed S: - ppts= observed in natural + unforced daily activities + unaware they're being observed= high ecological validity L: - ethical concerns (ppts can't give informed consent/have a right to withdraw as they're unaware of being observed - can't be replicated as researcher can't control variables --> method may be overly subjective

Question 91

controlled observations (techniques)

Answer 91

- one where researcher implements level of control + replicable procedures + sometimes on IV - procedures of observation= carefully designed + have predetermined behavioural categories to be measured - ppts know they're participating in a controlled observation as they are recruited for study + set a specific task

Question 92

covert observations (techniques)

Answer 92

- ppts= unaware that they're being observed - ppts may not be able to see researcher observing them - more likely to occur in naturalistic observation S: - high ecological validity as ppts= unaware so act in a natural real way --> investigator effects unlikely L: - ethical issues (ppts can't give informed consent) - problematic to be replicated

Question 93

overt observations (techniques)

Answer 93

- ppts are aware they're being observed (as they're informed in advance) - ppts may not be able to see researcher - most likely to occur in controlled lab env. S: - good ethics as inform ppt in advance + can withdraw L: - demand characteristics more likely + investigator effects= lowers validity - researcher bias (look for behaviours that support hypotheses etc)

Question 94

participant observation (techniques)

Answer 94

- researcher (+confederates) join group they are observing (become part of them) - ppts may be unaware that researcher is on 'outside' S: -obtain in-depth data as in close proximity to ppts= unlikely to overlook behaviours --> high validity as can access real thoughts, feelings + convos L: - researcher may have restricted view on what they observe + miss some important behaviours - if researcher too immersed they may lose objectivity as they may begin to identify with ppl they're observing= lowers validity

Question 95

non-participant observation (techniques)

Answer 95

- researcher= separate + apart from group they're observing - ppts may be aware or unaware they're being observed S: - objective distance kept= less bias/objective behaviour recordings = higher validity - demand characteristics + investigator effects= less likely L: - due to distance from 'action'= observation may lack key detail + insight= lacks explanatory power - could misinterpret some behaviours= lowers validity

Question 96

observational (design)

Answer 96

structured observation unstructured observation behavioural categories sampling methods

Question 97

structured observation (design)

Answer 97

- used normally in large samples in busy environments - allows researcher to observe few, specific + clearly defined behaviours rather than trying to make sense of too much info - emph on gathering of quantitative data - researchers conducting structured observations= interested in limited set of behaviours S: - quantitative data= quick + easy method + can be presented to show + compare trends - using predetermined categories= researcher less likely to become distracted L: - quantitative data only focuses on what and not 'why' - predetermined categories= only relevant behaviours to study may be ignored

Question 98

unstructured observation (design)

Answer 98

- used normally in small samples with more intimate environment where interpersonal interaction= focus - allows observers to observe everything= not restrictive - more flexible + open ended (don't use pre-determined behavioural categories) - gather more qualitative data S: - gain rich, insightful, detailed data= higher ecological validity - good to use on case study L: - personal + subjective= loses objectivity= unreliable --> researcher may be bias to certain ppts they get close to, may overlook key details - analysing data= time-consuming + down to interpretation

Question 99

behavioural categories

Answer 99

- used to record specific behaviours during observation session - categories design must be observable behaviours + have no ambiguity about what's being observed - categories have to be operationalised to ensure they're specific + can't be confused S: - clearly defined, unambiguous categories= subjectivity removed + researcher can be objective - can use more than one observer= increase inter-observer reliability L: - predetermined categories may be limiting

Question 100

sampling methods

Answer 100

- helps structure + organise observation session - event sampling- researcher records every time a behaviour from specific category occurs - time sampling- researcher records all behaviours during a set time frame e.g. at specific time they will look up and mark any behaviours/categories they see S: - event sampling= specific behaviours won't be overlooked - time sampling= allows for flexibility to record behaviours + gives opportunity to record only unexpected behaviours for future, less overwhelming L: - too many specific behaviours occurring at same time= complex + hard to capture= lower validity - time sampling misses behaviours outside time frame= lowers validity

Question 101

self-report techniques

Answer 101

questionnaires interviews

Question 102

questionnaires what are they?

Answer 102

- ppts answer a range of questions designed to collect their thoughts, feelings, attitudes, attributes + opinions - can consist of open (offers freedom of response, generates qualitative data) + closed questions (offers limited options for ppt response, generate quantitative data)

Question 103

questionnaires what must researcher consider when designing a questionnaire?

Answer 103

- Aim (purpose of it + how it will aid research) - length (too short= lacks data, too long= ppts will become bored + not answer with care/attention) - questions- need to be clear + concise, can't be leading (provide expected answers) + emotive (more neutral), can't be misunderstood questions: - fixed choice- asking ppt to choose from one of the options provided e.g. yes or no - libert scale- ppts agree of disagree with a statement - rating scale- ppts select value that corresponds to how strongly they feel about an idea/topic (e.g. scale of 1-10)- avoid double barrel questions

Question 104

questionnaires strengths + weaknesses

Answer 104

S: - quick, easy, convenient method of collecting data (from large samples, increase reliability) - use standardised questions= can be replicated= increase reliability - closed questions= provide quantitative data= easy to analyse + spot trends as can be presented graphically - open questions allows for expansion + explanations= explanatory power - can be completed without researcher present L: - tendency for ppl to under report negatives + over-report positive aspects of themselves= questionnaires can lead to ppl succumbing to social desirability bias (demand characteristics) - too little open questions= limits usefulness --> quantitative data lacks detail + insight - open questions= hard to analyse due to subjective nature= left to interpretation= lacks objectivity + reliability - ppts may have response bias/not read questions properly --> only few may be willing to fill out= sample bias --> need to be able to read + write

Question 105

interviews what is it?

Answer 105

- involves ppt answering range of questions put to them by a researcher --> one-to-one process (over phone, face-to-face, online etc) - designed to collect thought, feelings, attitudes, opinions

Question 106

types of interviews (structured)

Answer 106

- structured made up of pre-determined questions asked in fixed order- -open/closed questions - researcher writes down ppt response/records it S: standardised questions= interview can be replicated= limits researcher effects - may generate more quantitative data than unstructured= can be statistically analysed= increase reliability W: - pre-determined questions= restrictive= limits usefulness + richness of data

Question 107

types of interviews (unstructured + semi-structured)

Answer 107

unstructured - no prepared questions --> researchers have open mind as how interview will proceed - researcher writes/records ppt answers - interview= treated as a convo= ppts have freedom in responses etc --> normally has open questions --> produces qualitative data only S: - ecological validity- as ppl have freedom to respond how they want. Ppt has no manipulation from researcher - flexibility to pursue any interesting topics --> opens up insight W: - ppt may go in depth on irrelevant topics to research - researcher may lose objectivity due to intimate nature --> may feel too close to ppt + identify with them + present them in best positive light - interviewer bias - requires skilled interviewer semi-structured- e.g. job interview- list of questions worked out in advance BUT interviewers are free to ask follow-up questions etc

Question 108

designing interviews

Answer 108

- questions must be clear + concise + on-topic - record interview (make notes or audio/video record) - interviewer mustn't pass judgement - presence of interviewer (whether they seem interested or not) may effect amount of info provided (listening skills) - ppts wants/needs to feel comfortable in env + with interviewer

Question 109

content analysis what is it?

Answer 109

- method used to analyse qualitative data by turning it into quantitative data, does this by coding - it uses pre-recorded examples of spoken interactions, written word, media etc e.g. transcripts, text messages, interview audio recordings - aim= to summarise main ideas presented via structured methods CODING: assigns each behaviour to a 'code' that can be analysed numerically 1. researcher formulates research questions 2. researcher selects a pre-existing qualitative data source 3. researcher decides on coding categories e.g. terms for certain words 4. researcher works through data using a tally every time a behaviour etc from the category/code is shown 5. researcher checks reliability via: test-retest reliability (researcher runs content analysis again on same results + compares data) inter-rater-reliability (second person conducts content analysis on same sample + compares results

Question 110

content analysis strengths + weaknesses

Answer 110

S: - analyses qualitative + quantitative data = will have richer meaning which can be easily compared= reliable + valid - easy to understand - ethical as no manipulation- content used is often in the public domain. L: - uses material produced outside research process --> true context may not be known, researcher may be making assumptions= (affects validity) --> lacks detail no context - converting data from qualitative to quantitative= original data likely to be lost= lowers validity - subjective data as you decide on categories you're going to code

Question 111

thematic analysis what is it?

Answer 111

- method used to analyse qualitative data (data stays qualitative) - inductive method --> themes emerge from data, no hypothesis testing - allows researchers to analyse + report common themes/overarching ideas from a data set which may keep coming up - theme= only feature of data which recurs throughout - researcher identifies themes in data --> reviews them to see if they explain behaviour + answers research --> then categorises + defines each theme e.g. looking at themes in holiday recommendations such as temperature, stereotyping (family or young party holiday), accommodation, culture etc)

Question 112

thematic analysis strengths + weaknesses

Answer 112

s: - solely qualitative data= provides insight into 'why'= ecological validity - researcher can quote directly from source --> real, subjective l: - time-consuming - researcher prone to confirmation bias (overlooks themes which don't align with their focus + ideas)