Research methods Flashcards
What is the difference between an aim and a hypothesis?
- An aim is a general statement made by the researcher which tells us what they plan on investigating
- A hypothesis is a precise statement which clearly states the relationship between the variables being investigated
What is the experimental method?
While all other variables are held constant, one variable is manipulated (IV) and the effect of this on another variable is measured (DV)
What is the difference between a directional and non-directional hypothesis?
- A directional hypothesis states which way you think the results are going to go
E.g. Eating smarties will significantly improve an individual’s dancing abilities - A non-directional hypothesis simply states that there will be a difference between the two groups/conditions but does not say which will be greater/smaller, quicker/slower etc
E.g. There will be a difference in male and female performance in a driving test
Used when there is little or no research or the findings are ambiguous
What is a natural experiment?
A natural experiment is an experiment in which the IV is not brought about by the researcher hence would have happened even if the researcher had not been there e.g. if studying reactions to earthquakes
What are the limitations of a natural experiment? (A03)
- Natural occurring events: may be rare so these experiments are not likely to be replicable - hard to generalise findings
- Very difficult to randomise participants into groups: confounding and extraneous variables become a problem
What are true experiments?
True experiments control the variables under investigation, and randomly allocate participants to groups
Lab and field experiments are both true experiments
What is an extraneous variable?
An extraneous variable is any variable that you’re not investigating that can potentially affect the outcomes of your research study
Doesn’t vary systematically with the IV - nuisance variables
What is a confounding variable?
A confounding variable is a variable other than the independent variable that systematically affects the dependent variable
Difficult for the researcher to be sure of the origin of the impact of the DV as the confounding variable could have been the cause
What is the difference between randomisation and standardisation?
- Randomisation is the use of chance to reduce the effect of bias from investigator effects
- Standardisation describes using the exact same formalised procedures and instructions for every single participant involved in the research process - eliminates non-standardised instructions as possibly extraneous variables
What is operationalisation?
Making sure your variables are in a form that can be easily tested
What are the strengths of a natural experiment? (A03)
+ Provides opportunities: for research that would have otherwise been impossible due to practical/ethical reasons
+ High external validity: dealing with real-life issues
What are the 4 types of experiments?
Laboratory, field, natural, quasi
What is a lab experiment?
A lab experiment is an experiment that takes place in a special environment whereby different variables can be carefully controlled
What are demand characteristics?
Aspects of the study which lead participants to guess the aim of the study and form expectations about how they should behave
What are the 3 types of experimental design?
Independent groups
Repeated measures
Matched pairs
What is a field experiment?
A field experiment is an experiment conducted in a more natural environment, not in a lab but with variables still being well controlled
What are the strengths and weaknesses of a field experiment?
Strengths:
- Naturalistic: so more natural behaviours hence high ecological validity
- Controlled IV
Limitations:
- Ethical considerations: invasion of privacy and likely to be no informed consent
- Loss of control: due to extraneous variables hence precise replication not possible
What is independent groups design?
Two different groups experience two different conditions - the IV is naturally occurring
What is a strength and weakness of quasi experiments? (A03)
+ Controlled conditions: hence replicable, likely to have high internal validity
- Cannot randomly allocate participants: may be confounding variables presented - makes it harder to conclude that the IV caused the DV
What are the weakness of lab experiments? (A03)
- Experimenter’s bias: can affect results and participants may be influenced by these expectations
- Low ecological validity: high degree of control makes situation artificial, unlike real life
What is the difference between external validity and internal validity?
- External validity refers to the extent to which the results of a study can be generalized to other settings (ecological validity), other people (population validity), and over time
- Internal validity is a measure of whether results obtained are solely affected by changes in the variable being manipulated (i.e. by the IV) in a cause-and-effect relationship
What is a quasi experiment?
- Quasi experiment: the IV has not been determined by the researcher, instead it naturally exists, e.g. gender difference studies
- IV is a personal characteristic
What are the strengths of a lab experiment? (A03)
+ High degree of control: all variables are controlled, IV has been precisely replicated - greater accuracy
+ Replication: researchers can repeat experiments and check results
What are the strengths of independent groups design?
+ Order effects can’t be observed as no participants are used in more than one condition
+ Data collection is less time-consuming - all conditions of the experiment can be conducted simultaneously
What are the weaknesses of independent groups design?
- Different participants need to be recruited for each condition - expensive
- Risk of participant variables affecting results between conditions, not just manipulation of the IV
What is an example of an independent groups experiment?
A study on sleep that explores how different amounts of sleep affect people’s reaction times. Whilst one group had 10 hours of sleep per night, the other group had 3
- IV: the amount of sleep (the manipulated variable).
- DV: (the measured variable) was their recorded reaction time
What is repeated measures design?
All participants take part in all conditions - same participants allocated to all groups
What are the strengths of repeated measures design?
+ Results won’t be subject to participant variables
+ Same participants used twice so extra participants do not need to be recruited
What are the weaknesses of repeated measures design?
- Risk of observing order effects, but this risk be reduced by counterbalancing (controlling order of variables so each order combination occurs the same number of times)
- If a participant drops out, data will be lost from all conditions of the experiment, not just one
What is an example of a repeated measures experiment?
- A study investigates whether Quizlet helps A-level psychology students better than traditional textbooks, assessing learning with tests
- If the researchers conduct a repeated measures experiment, all participants will use Quizlet and standard textbooks
What is matched pairs design?
A pair of participants are matched bases on key variables (age ,gender etc). One member is put in the control group and the other in the experimental group
What are the strengths of matched pairs design?
+ Order effects will not be observed as participants only take part in one condition
+ Reduced risk of participant variables affecting results between conditions - tailored participant-matching process
What are the weaknesses of matched pairs design?
- Different participants needed for each condition- difficult and expensive
- Matching is a complex process - difficult to match participants identically, so identical twins are often used
What is an example of a matched pairs experiment?
A study of 100 people for a new diet - each subject would be paired with another subject similar to them and then randomly allocated to either the control or experimental group
What are the 3 order effects?
- Demand characteristics- subtle hints that suggest to the participant what the experimenter predicts or hopes to find in the study
- Boredom
- Fatigue
What is random sampling?
This method gives every member of the target group an equal chance of being selected for the sample by assigning a number to each member, and then selecting from the pool using a random number generator
What are the strengths of random sampling?
+ Representative - each member has the same probability of being selected
+ No researcher bias - researcher has no influence over who is picked
What are the weaknesses of random sampling?
- Time consuming - need to have a list of the population (sampling frame) and then contacting them takes time
- Volunteer bias - participants can refuse to take part so can end up with an unrepresentative sample
What is opportunity sampling?
Participants happen to be available at the time which the study is being carried out so are recruited conveniently
What are the strengths and weaknesses of opportunity sampling?
+ Easy method of recruiting which is time saving and less costly
+ Covnenient
- Not representative of the whole population -findings can’t be generalised
- Researcher bias is presented as they control who they want to select
What is systematic sampling?
A predetermined system is used whereby every nth member is selected from the sampling frame consistently
What is a strength and weakness of systematic sampling?
+ Avoids researcher bias and usually fairly representative of the population
- Not truly unbiased unless you use a random number generator then start the systematic sample
What is stratified sampling?
- Stratified sampling involves selecting participants in such a way as to recreate the same proportions of those sub-groups (strata) that exist in the population
- Then select the sample from each strata using random number generators
What are the strengths of stratified sampling?
+ No researcher bias - the selection within each strata is done randomly
+ Produces representative data due to the proportional strata so generalisation is possible
What are the weaknesses of stratified sampling?
- Time consuming to identify strata and contact people from each
- Not completely representative - the identified strata can’t reflect all differences between the people of the wider population
What is volunteer sampling?
Involves self-selection whereby the participant offers to take part either in response to an advert or when asked to
What are the strengths and weaknesses of volunteer sampling?
Strengths:
- Easy and not time-consuming - quick access to willing participants
- As participants are willing to take part, they are more likely to cooperate in the study
Weaknesses:
- Volunteer bias - may attract a particular profile of a person (keen, curious) - generalisation is affected
What are pilot studies?
- Small, trial versions of proposed studies to test their effectiveness and make improvements
- They allow for modification of methodology where necessary
What are the strengths of pilot studies?
+ A pilot study allows a researcher to decide whether or not it will be worthwhile to conduct a planned study on a larger scale
+ A pilot study also provides the researchers with practice of running the study before the full data gathering begins, allowing all aspects of the study to go more smoothly
What are the ethical standards in psychology?
Can Do Can’t Do With Participants
C- informed Consent: participants must be told the aims of the experiment and any possible risks they may be subject to by participating
D- Deception: the act of deliberately witholding information from participants
C- Confidentiality & privacy:
D- Debrief: telling participants the general aim of the study
W- right to Withdraw: at any point in the study
P- Protection from harm: participants must be protected from physical and psychological harm
What are the 3 types of consent?
Retrospective
Presumptive
Prior general consent
What is retrospective consent?
Participants are asked for their consent after they have taken part in the study
What is presumptive consent?
When a researcher gathers opinions from a group like the participants in the study but does not inform the actual participants
What is prior general consent?
Participants give consent to take part in many studies whereby one of them involves deception, so effectively they are consenting to being deceived
What are the different observational techniques?
naturalistic, controlled, overt, covert, participant, non-participant
What is naturalistic observation?
Naturalistic: takes place in the setting or context where the target behaviour would usually occur and all aspects of the environment are free to vary
What is a strength and weakness of naturalistic observation?
+ High external validity as findings can be generalised to everyday life - studied in natural environment
- Lack of control over research situation makes replication hard and introduces extraneous variables
What is a controlled observation?
Controlled: likely to be caried out in a psychology lab, in a carefully controlled and structured environment (no IV or DV) e.g Bandura’s Bobo doll study
What is a strength and weakness of
controlled observations?
+ Extraneous variables are less of a factor due to high levels of control so replication is easier
- May produce findings that can’t be readily applied to real-life settings
What is an overt observation?
Overt: participants know their behaviour is being observed and they have given informed consent - the observer is clearly visible
What is a strength and weakness of an overt observation?
+ More ethically acceptable
- The knowledge participants have that they’re being observed could influence their behaviour - demand characteristics
What is a covert observation?
Covert: participants are unaware they are the focus of the study and their behaviour is observed in secret
What is a strength and weakness of a covert observation?
+ Participants don’t know they’re being watched which removes participant reactivity and demand characteristics - increased validity
- Unethical as people may not wish to have their behaviours recorded
What is a participant observation?
Participant: the researcher joins in with the situation being observed
What is a strength and weakness of a participant observation?
+ The researcher experiences the situation as the participants do which gives them increased insight into the lives of those being studied - increases validity
- The researcher may come to identify too strongly with participants and lose objectivity (going native)
What is a non-participant observation?
Non-participant: the researcher doesn’t actively become involved in the behaviour being studied - separate from the research situation and doesn’t engage
What are the strengths and weakness of a non-participant observation?
+ Researcher can be more objective as less likely to identify with participants
- Open to observer bias e.g. stereotypes
- Researcher may lose some valuable insight
What are the strengths and weaknesses of structured vs unstructured observations?
Structured:
+ Use of behavioural categories - recording data is easy & systematic
+ Produces numerical data - easy to analyse & compare
Unstructured:
+ Richness & depth of detail
- Observer bias - due to lack of operationalised behvaioural categories
- Qualitative data - hard to record & analyse
What are the strengths and weaknesses of behavioural categories?
- Categories must be clear & unambiguous - observable, measurable, & self-evident -> shouldn’t require further interpretation
- All possible forms of target behaviour should be included in the checklist - no ‘dustbin’ category
- Categories should be exclusive and not overlap
What is time sampling?
Time sampling: the recording of a behaviour within a time frame that is pre-established before the observational study
What is a strength and weakness of time sampling?
+ Reduces the number of observations that have to be made so less time consuming
- The small amount of data you collect within that time frame ends up being unrepresentative of the observation as a whole
What is event sampling?
Event sampling: this involves the counting of the number of times a particular behaviour is carried out
What is a strength and weakness of event sampling?
+ Good for infrequent behaviours that are likely to have been missed if time sampling was used
- Hard to distinguish the end and begininning of a behaviour
What are the weaknesses of event sampling?
- Counting errors if the behaviour is very frequent
- Difficult to judge the beginning and ending of a behaviour
- If complex behaviour is being observed, then important details may be overlooked
What are behavioural categories?
- Involves breaking the target behaviour down into components that can be observed and measured
- When conducting structured observations, psychologists have to decide which specific behaviours should be examined
- They operationalise the behaviour through behavioural categories
What are self-report techniques and what are the different types?
They are a non-experimental research method in which participants report on their own thoughts or behaviour without researcher inference
e.g. questionnaires, interviews (structured or unstructured)
What are questionnaires?
Questionnaires: involve a pre-set list of written questions to which a participant responds - a study that uses a questionnaire is often called a survey
What are the strengths of questionnaires?
+ Cost effective: gather large amounts of data quickly as they can be distributed to large numbers of people
+ Less effort: can be conducted without the researcher being present (postal questionnaire)
+ Easy to analyse
What are the weaknesses of questionnaires?
- Social desirability bias: particpants may lie to give answers expected of them (demand characteristic)
- Leading questions: questions worded in a way that encourages a certain answer from participants
- Misunderstanding: participants could misinterpret questions
What is the difference between open and closed questions?
Open: questions where there is no fixed choice of response
Closed: questions where there is a fixed choices of responses
What are the different types of closed question questionnaires?
Likert scale: the respondent indicates agreement with a statement, ranges from strongly agree to strongly disagree
Rating scale: works similarly but gets respondents to identify a value that represents their strength of feeling about a particular topic
Fixed choice scale: the question includes a list of possible options and respondents are required to indicate those that apply to them
What is the difference between structured interviews and non-structured interviews?
Structured interview: made up of a predetermined set of questions that are asked in a fixed order
Unstructured interview: more like an everyday conversation - interviewer may begin with certain planned questions but then follow these up or ask other questions spontaneously
What are the strengths of interviews?
+ Unstructured interviews provide potential to gather rich and detailed information from each participant
+ The conversational nature of unstructured interviews is best suited to discussing complex/sensitive issues - participants are more likely to relax and give better responses
+ Structured interviews are easy to replicate
What are the weaknesses of interviews?
- Time and expense involved when training interviewers
- Social desirability bias can be a problem with self-report techniques, i.e. participants give responses that are thought to be the most socially acceptable, rather than necessarily truthful.
- Interview data can be a time-consuming task to analyse and interpret when it is so detailed
What are the do’s and dont’s when constructing interviews?
- Interview schedule
- Standardised - reduces interviewer bias
- Single or group interviews
- Reminder of ethical issues
- Avoid leading questions
- Avoid overuse of jargon
- Avoid double-negatives
What is the difference between qualitative and quantitative data?
Qualitative: non-numerical data that uses words to give a full description of what people think
or feel
Quantitative: data that is displayed numerically
What are the strengths and weakness of qualitative data?
+ More richness and depth of detail
+ Allows participants to further develop their opinions hence has greater external validity
+ More meaningful insight into participants views
- Difficult to analyse and make comparisons with other data
- Researcher bias as conclusions made rely on the subjective interpretations of the researcher
What are the strengths and weaknesses of quantitative data?
+ Can be analysed statistically so can be converted to graphs or charts
+ Easy to compare with other data
- Lack of depth in detail
- Participants aren’t able to develop their opinions so results have low external validity
What is the difference between primary and secondary data?
- Primary data: information is obtained firsthand by the researcher for the purpose of the investigation
- Secondary data: when information is collected by someone else other than the researcher e.g. government statistics, journals
What are the strengths and weaknesses of primary data?
+ Targets the exact information the researcher needs so the data fits their aims and objectives
- Requires time and effort
- Can be expensive
What are the strengths and weaknesses of secondary data?
+ Easily accessible
+ Inexpensive to collect and requires minimal effort
- Likely that data is outdated or incomplete
- Data may be unreliable - researcher wasn’t there when the study was being conducted so could be unsure of validity of the results
What is meta-analysis?
Meta-analysis: when the researcher combines results from many different studies and uses all the data to form an overall view of the subject they are investigating
What is a strength and weakness of meta-analysis?
+ More generalisablity is possible as a larger amount of data is studied
- Publication bias: when the researcher intentionally doesn’t publish all the data from the relevant studies but instead chooses to leave out negative results - gives a false representation of what the researcher was investigating
What is are the strengths and weaknesses of the mean?
+ Sensitive as it makes use of all values
- Influenced by extreme values so it can be unrepresentative
What are the strengths and weaknesses of the median?
+ Unaffected by extreme values
- Not as sensitive as the mean as it doesn’t use all values
What are the strengths and weaknesses of the mode?
+ Useful for data in categories
- Not useful when there are several modes
What are the strengths and weaknesses of the range?
+ Easy to calculate
- Affected by extreme values
- Doesn’t use all values
What are the strengths and weaknesses of standard deviation?
+ Precise measure where all data values are taken into account
- Difficult to calculate
- Affected by extreme values
What are correlation coefficients?
This value determines the strength and relationship between two variables
- Negative correlation: less than 0
- Positive correlation: more than 0
- Zero correlation: equal to 0
What are the strengths of correlations?
+ Can be used as starting points to assess patterns between covariables before committing to conducting an experimental study
+ Quick and economical to carry out
What are the weaknesses of correlations?
- Difficult to establish a cause and effect relationship as only an association is found
- Third variable problem is presented: a third variable which the researcher is unaware of that is responsible for the relationship between the co-variables
- Correlations tend to be misused or misinterpreted especially when made public by the media
What is a normal distribution?
A symmetrical spread of frequency data that forms a bell-shaped pattern. The mean, median and mode are all located at the highest peak
What is a skewed distribution? What are the two types?
Skewed distribution: a spread of frequency data that is not symmetrical, where the data clusters at one end
Positive skew
Negative skew
What is the difference between a positive and negative skew?
Positive: A type of frequency distribution in which the long tail is on the positive (right) side of the peak and most of the distribution is concentrated on the left
Mode < mean, median
Negative: A type of frequency distribution in which the long tail is on the negative (left) side of the peak and most of the distribution is concentrated on the right.
Mode > mean, median
What is the distinction between bar charts and histograms?
- Bar charts are used for discrete data (categorical)
- The bars don’t touch which show we are dealing with separate conditions
- Histograms are used for continuous data
- The bars touch
What is statistical testing?
Provides a way of determining whether hypotheses should be accepted or rejected. In psychology, they tell us whether differences or relationships between variables are statistically significant or have occurred by chance.
What are the different statistical tests?
(Carrots Should Come Mashed With Swede Under Roast Potatoes)
- Chi-squared
- Sign test
- Chi-squared
- Mann Whitney
- Wilcoxon
- Spearman’s Rho
- Unrelated-t test
- Related-t test
- Pearson’s r test
- Remember NOI down the side
What is the sign test?
What is the significance value?
A statistical test used to analyse the difference in scores between related items.
0.05
What are the 3 conditions in order to use the sign test?
- A difference between variables
- Used repeated measures design
- Collected nominal data
When might a researcher employ a 1% significance value?
- When research may involve human cost
- When a particular investigation is a one-off and there is no possibility of the research being repeated
What 3 things must you look for when looking at a critical value table?
- One-tailed or two-tailed hypotheses
- Number of participants
- Significance level (0.05)
How do you carry out the sign test?
- Calculate difference between two sets of data
- Add up total number of “+’s” and “-‘s”
- The least frequent sign is S value - calculated value
- Go to critical value table - calculated ‘S’ value must be equal to or less than the critical value to be significant
What is the difference between nominal, ordinal and interval data?
- Nominal: used when data is put into categories e.g.
number of people who chose a high-fat snack/people who chose a low-fat snack - Ordinal: used when participant scores can be arranged in order e.g. 1st 2nd, 3rd in terms of the ranking of scores
- Interval: provides the most sensitive & sophisticated level of measurement - there is an equal interval between each unit of measurement e.g. centimetres
What is the significance of the S-value?
In a given study, the smaller the S-value, the greater the difference in before and after scores -> the more likely we are to reject the null hypothesis
What is peer review?
The assessment of scientific work by experts in the same field, it is done to make sure all research intended to eventually be published is of high quality
What are the main purposes of peer review?
- To know whether research is worthwhile hence funding can be allocated to it
- To validate the relevance and quality of research -> prevents fraudulent research being released to the public
- To suggest possible improvements or amendments to the research study
What is reliability
- Measure of consistency
- A test/study is reliable if the same results are consistently found when it is replicated under the same conditions
What are the two types of reliability?
Internal reliability: The extent something is consistent with itself
External reliability: The extent a test measure is consistent over time
What are the ways of assessing reliability?
- Test-retest: measures external reliability
- Split-half method measures internal reliability
- Inter-observer reliability
What are the 2 ways of assessing reliability of questionnaires?
- Test-retest: adminster the same test/questionnaire to the same person/people on different occasions
- If same result is found per participant = external reliability
- Reliable = correlation coefficient of +0.8
- Split half: researcher splits the test in half & analyses the responses given to the first half of the questionnaire compared to the second half - similar responses in both halves = internal reliability
How is reliability assessed in observations?
- Inter-observer reliability: the level of consistency between two or more trained observers when they conduct the same observation - record their observations separately + correlated at the end to assess reliability
- All observers must agree on the behaviour categories + how they are going to record them before observation begins
- Observation conducted separately to avoid conformity
After observational period: - Observers compare the 2 independent data sets (often designed as a tally chart)
- They then test the correlation between the 2 sets - strong positive correlation shows good inter-observer reliability + behaviour categories are reliable
What are the different ways of improving reliabilty?
- Questionnaires: not complex or ambiguous questions (avoid misniterepetation), replace open questions with closed ones
- Interviews: same interviewers, all interviewers are trained to avoid leading & ambiguous questions, structured interviews
- Experiments: lab studies most reliable - controlled conditions; standardised procedure; random allocation to conditions; control group for comparison; generate quantitative data
- Observations: behavioural categories are operationalised, measurable & self-evident (no overlaps)
What is validity?
- Measure of legitimacy and accuracy
- The extent to which a test/measurement tool accurately measures what the study sets out to
What is the difference between external and internal validity?
- Internal validity: measures whether the results are due to to the manipulation of the independent variable and not confounding variables
- External validity: measures whether the results can be generalised beyond the research setting
What are the other types of validity?
Ecological validity: whether it can be generalised to other settings
Population validity: whether it can be generalised to other people
Temporal validity: when it can be generalised over time
What are the different ways of assessing validity?
- Face validity: assesses whether something is what it looks like, to what extent the item looks like what it measures
- Concurrent validity: assesses through correlation, correlating the scores from research already existing and known to be valid
- Predictive validity: Assesses validity by predicting how well a test does at predicting future behaviour
- Temporal validity: Assesses how valid it remains over time
What are the different ways of improving validity?
- Experimental research: control group (shows changes in DV were from IV), standardisation (minimises participant reactivity + investigator effects), single-double blinds
- Questionnaires: anonymity (social desirability), lie-scale
- Observations: covert observations, behavioural categories
- Qualitative research: interpretive validity, triangulation (using many different sources as evidence)
What are case studies and how is data collected on them?
- Case studies are detailed and in-depth investigations of a small group or an individual
- They allow researchers to examine individuals in great depth
- Data is often collected through interviews or observations, generating mostly qualitative data
- Most case studies tend to be longitudinal i.e. ppts experience/progress is tracked & measured
What are the weaknesses of case studies?
- Results are not generalisable or representative due to (usually) only one person being the focus of the study
- Researcher may be biased in their interpretation of the information
- Often case studies rely on their ppts having a good memory which means that information/details can be missed which would impact the validity of the findings
What are the strengths of case studies?
- Holistic approach - the whole individual & their experiences are considered
- Allows researchers to study unique behaviours & experiences which would be unethical or impossible to manipulate in controlled conditions
- Case studies provide rich, in-depth data which is high in explanatory power
- Case studies may generate hypotheses for future study, and even one solitary, contradictory instance may lead to the revision of an entire theory
What is content analysis?
A research technique that enables the indirect study of behaviour by examining communications that people produce (eg. In emails, TV, Film and other media)
What is thematic analysis?
- A qualitative approach to analysis that involves identifying implicit or explicit ideas within the data
- Themes will often emerge once the data has been coded
What is coding (research methods)?
The stage of content analysis in which the data being studied is put into categories (eg. words, sentences, phrases, etc.)
What are the stages of conducting a content analysis?
- The researcher chooses the research question
- They select a sample of pre-existing qualitative research e.g. interview transcripts, diaries, video recordings
- The researcher will decide on the coding of the categories/coding units
- The researcher works through the data creating a tally which shows the categories/codes that are most common in the qualitative data
How does the researcher test for reliability after conducting a content analysis?
- Test-retest reliability: run the content analysis again on the same sample and compare the results; if they are similar then this shows good test-retest reliability
- Inter-rater reliability: a second rater conducts the content analysis with the same coding categories & data and compares them; if results are similar = good inter-rater reliability
What are the strengths of content analysis?
- Reliability is established as a content analysis is easily replicable
- Allows statistical analysis to be conducted
- Not overly time-consuming compared to thematic analysis of qualitative data
- Complements other research methods and can be used to verify results from other research
What are the weaknesses of content analysis?
- Researcher bias can happen as the researcher has to interpret the data
- May lack validity due to extraneous variables, e.g., diary entries tend to be highly subjective
- The data is purely descriptive - no explanatory power
- Lacks causality as the the data was not collected under controlled conditions
- Results can often be flawed due to the over-representation of certain events & using material that is already available - e.g. negative events usually have more coverage than positive - this could skew the data to give an invalid representation of behaviour
How do you write a debrief?
- Thank ppts
- Explain use of deception & why it was necessary
- Explain purpose of study & ppts role within it
- Remind ppts that their data is anonymous but can still be withdrawn
- Tell them to get in touch if they’re upset, have questions, or want to withdraw
How do you write a consent form?
- Include detail of what ppts expect to happen: how long is the study for, aim of the study, what will happen to ppts
- Refer to ethical issues: informed consent e.g. signature
- Appropriate format: place to sign, date, name, yes/no options, ask for consent e.g. ‘I understand that..’
What are the 7 features of a science? Define them.
- Hypothesis testing
- Empirical evidence: when we collect evidence from direct observations
- Falsifiability: it’s possible for the hypothesis to be proven false
- Replicability
- Control: a level of IV which the researcher is not manipulating
- Objectivity: not letting personal bias affect the way you carry out your experiment
- Theory construction
What are the different types of extraneous variables and how do you control for them?
- Investigator effects: the researcher influences the behaviour of the ppts & results
- Participant variables: personal characteristics of the ppts that affect DV
- Situational variables: EVs that are features of the external environment
Controlled with:
- Standardisation- making an EV the same for all ppts
- Matching: making sure a particular characteristucs of the ppts is divided equally across groups - ppt variables
- Random allocation - ppt variables
What are the problems with study design you should look for? (HINT: BIASES)
- Observer/social desirability Bias
- Investigator effects
- Random Allocation
- Standardisation
- Experiment design
- Sampling method
What is the difference between a Type 1 & Type 2 error?
- Type 1 error: when a researcher rejects a null hypothesis that is true
- Type 2 error: when a researcher rejects a null hypothesis that is false
