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whereas qualitative data provide non-numerical descriptions of experiences, meanings or behaviour."},{"text":"Psychology data can be qualitative - numerical - or quantitative - descriptive.","correct":false,"explanation":"The two terms have been reversed. Quantitative data are numerical, while qualitative data are descriptive and usually expressed through words rather than numbers."},{"text":"Psychology data can be primary - numerical - or secondary - descriptive.","correct":false,"explanation":"Primary and secondary describe the source and purpose of data, not their form. Numerical data are quantitative, while descriptive data are qualitative."},{"text":"Psychology data can be objective - numerical - or subjective - descriptive.","correct":false,"explanation":"Objectivity concerns whether findings are influenced by personal judgement. The correct distinction is quantitative for numerical data and qualitative for descriptive data."}]},{"id":"0e01f768-ca1d-4056-9c91-9438644dab1d","cardType":"cloze","points":null,"front":"The primary/secondary distinction depends on [ ], not whether data are [ ].","back":"The primary/secondary distinction depends on source and purpose, not whether data are quantitative or qualitative.","mcqOptions":[{"text":"The primary/secondary distinction depends on source and purpose, not whether data are quantitative or qualitative.","correct":true,"explanation":"Data are classified as primary or secondary according to who collected them and why, independently of whether their form is quantitative or qualitative."},{"text":"The primary/secondary distinction depends on numerical form, not whether data are reliable or valid.","correct":false,"explanation":"Numerical form determines whether data are quantitative, not whether they are primary or secondary. That distinction depends on the data’s source and original purpose."},{"text":"The primary/secondary distinction depends on research method, not whether data are first-hand or pre-existing.","correct":false,"explanation":"First-hand versus pre-existing data is central to this classification, whereas any research method can produce primary data. The distinction depends on source and purpose."},{"text":"The primary/secondary distinction depends on source and purpose, not whether data are reliable or valid.","correct":false,"explanation":"Although source and purpose correctly determine the primary/secondary classification, the contrasted categories should be quantitative and qualitative. Reliability and validity assess research quality instead."}]},{"id":"1c2844e4-ac33-4873-884a-e39645f0c094","cardType":"cloze","points":null,"front":"Primary data are collected [ ] for the [ ] of the current study.","back":"Primary data are collected first-hand for the specific aims of the current study.","mcqOptions":[{"text":"Primary data are collected first-hand for the specific aims of the current study.","correct":true,"explanation":"Primary data are gathered directly by the current researcher specifically to answer the aims or research questions of the study being conducted."},{"text":"Primary data are collected second-hand for the specific aims of the current study.","correct":false,"explanation":"Second-hand data come from an existing source and are therefore secondary. Primary data must be collected first-hand for the specific aims of the current study."},{"text":"Primary data are collected first-hand for the original aims of a previous study.","correct":false,"explanation":"Data gathered for a previous study’s aims are secondary when reused. Primary data are collected first-hand for the specific aims of the current study."},{"text":"Primary data are collected indirectly for the general aims of the current study.","correct":false,"explanation":"Indirect collection and broad relevance do not define primary data. They must be collected first-hand to address the current study’s specific aims."}]},{"id":"440b3da3-8254-4518-9430-e8b2de6cd2b6","cardType":"basic","points":1,"front":"Why were Loftus and Palmer's speed estimates primary data?","back":"They were collected directly for that study.","mcqOptions":[{"text":"They were collected directly for that study.","correct":true,"explanation":"Loftus and Palmer collected participants’ speed estimates directly as part of their own investigation, making the estimates primary data produced for that specific study."},{"text":"They were taken from records for that study.","correct":false,"explanation":"Using records that already existed would make the estimates secondary data. Loftus and Palmer instead collected the estimates directly from participants for their investigation."},{"text":"They were published previously before that study.","correct":false,"explanation":"Previously published estimates would be pre-existing secondary data. The estimates were primary because the researchers collected them directly for the study’s own aims."},{"text":"They were numerical responses from that study.","correct":false,"explanation":"Being numerical makes the estimates quantitative, but does not make them primary. They were primary because they were collected directly for that particular study."}]},{"id":"9846bfc8-cdc6-4862-9407-63f85c42d6a6","cardType":"cloze","points":null,"front":"Secondary data [ ] before the current research, often collected for [ ].","back":"Secondary data already exist before the current research, often collected for a different purpose.","mcqOptions":[{"text":"Secondary data already exist before the current research, often collected for a different purpose.","correct":true,"explanation":"Secondary data predate the current investigation and were commonly gathered by another researcher or organisation to meet aims different from those of the current study."},{"text":"Secondary data are newly collected before the current research, often collected for the same purpose.","correct":false,"explanation":"Newly collecting data for the current aims would produce primary data. Secondary data already exist before the research and were often gathered for a different purpose."},{"text":"Secondary data already exist before the current research, often collected for the current purpose.","correct":false,"explanation":"Pre-existing data are secondary, but they were not collected specifically for the current research. They were often originally gathered for a different purpose."},{"text":"Secondary data are gathered first-hand before the current research, often collected for a specific purpose.","correct":false,"explanation":"First-hand collection for the current study defines primary data. Secondary data already existed before the research and were often collected for another purpose."}]},{"id":"08e207c1-18ed-417f-9594-ff28ada6d383","cardType":"basic","points":1,"front":"What source-test question helps decide if data are primary?","back":"Were the data collected first-hand for this exact study?","mcqOptions":[{"text":"Were the data collected first-hand for this exact study?","correct":true,"explanation":"Primary data must be gathered first-hand specifically for the current investigation, so this question checks both the data’s source and their intended purpose."},{"text":"Were the data expressed numerically in this exact study?","correct":false,"explanation":"Numerical expression identifies quantitative data, not primary data. The relevant test is whether the data were collected first-hand specifically for the current study."},{"text":"Were the data collected previously for another study?","correct":false,"explanation":"Data collected previously for another study are secondary rather than primary. Primary data are collected first-hand for the exact study now being conducted."},{"text":"Were the data judged reliable in this exact study?","correct":false,"explanation":"Reliability concerns consistency and can apply to either primary or secondary data. Primary status depends on first-hand collection for the exact current study."}]},{"id":"262f8b29-3f75-42e5-9b1e-94013c53872a","cardType":"basic","points":1,"front":"A teacher analyses old school attendance records. What data type is this?","back":"Secondary data - the records already existed.","mcqOptions":[{"text":"Secondary data - the records already existed.","correct":true,"explanation":"The attendance records were created before the teacher’s current analysis, so they are pre-existing information being reused as secondary data."},{"text":"Primary data - the teacher collected the records.","correct":false,"explanation":"Accessing or analysing records is not the same as first-hand data collection. Because the attendance records already existed, they are secondary data."},{"text":"Quantitative data - the records already existed.","correct":false,"explanation":"Attendance figures may be quantitative, but that describes their numerical form rather than their source. Because the records already existed, they are secondary data."},{"text":"Qualitative data - the records describe attendance.","correct":false,"explanation":"Attendance records typically contain numerical counts, but qualitative versus quantitative is not the key distinction here. Their pre-existence makes them secondary data."}]},{"id":"b8d7eff7-f51f-423f-b731-d6634f0c3804","cardType":"basic","points":2,"front":"What is the main strength of primary data?","back":"Control over what, how, who and when to measure.","mcqOptions":[{"text":"Control over what, how, who and when to measure.","correct":true,"explanation":"Collecting primary data lets researchers tailor variables, procedures, samples and timing to their own aims, giving them substantial control over the resulting evidence."},{"text":"Convenience over what, how, who and when to measure.","correct":false,"explanation":"Primary data collection is often time-consuming rather than especially convenient. Its main strength is researcher control over what is measured and how, from whom and when."},{"text":"Economy over what, how, who and when to measure.","correct":false,"explanation":"Primary data can be expensive to collect, whereas reusing secondary data is often more economical. The key advantage of primary data is control over measurement."},{"text":"Objectivity over what, how, who and when to measure.","correct":false,"explanation":"Collecting data first-hand does not automatically remove researcher bias or guarantee objectivity. Its main strength is control over the variables, procedures, participants and timing."}]},{"id":"1d46080a-262c-4f81-8b7c-8bce2fa8cae9","cardType":"basic","points":1,"front":"How could “memory” be operationalised in the notes' example?","back":"As the number of words correctly recalled from a list.","mcqOptions":[{"text":"As the number of words correctly recalled from a list.","correct":true,"explanation":"Memory is made measurable by counting how many words each participant recalls correctly, producing an objective score that can be compared across participants or conditions."},{"text":"As the time taken to read all the words from a list.","correct":false,"explanation":"Reading time measures processing or reading speed rather than memory. Memory is operationalised as the number of words correctly recalled from the list."},{"text":"As the number of words originally presented from a list.","correct":false,"explanation":"The number presented is a feature of the task, not a measurement of participants’ memory. The correct measure is the number of words correctly recalled."},{"text":"As the confidence participants report afterwards from a list.","correct":false,"explanation":"Self-reported confidence may not correspond to actual recall performance. Memory is operationalised objectively by counting the number of words correctly recalled from the list."}]},{"id":"76ec2525-9b02-4c77-9b04-89f71cfcde6e","cardType":"basic","points":2,"front":"How do standardised procedures support reliability?","back":"Same instructions/tasks reduce procedural variation.","mcqOptions":[{"text":"Same instructions/tasks reduce procedural variation.","correct":true,"explanation":"Standardising instructions and tasks ensures that every participant experiences the same procedure, reducing procedural variation and making the study easier to replicate consistently."},{"text":"Same instructions/tasks reduce participant variation.","correct":false,"explanation":"Standardisation does not remove individual differences between participants. It supports reliability by reducing procedural variation, so differences are less likely to result from inconsistent methods."},{"text":"Same instructions/tasks reduce ecological validity.","correct":false,"explanation":"Ecological validity concerns how well findings represent real-life behaviour, not procedural consistency. Standardised instructions support reliability by reducing procedural variation."},{"text":"Same instructions/tasks reduce population validity.","correct":false,"explanation":"Population validity concerns whether findings generalise to other people. Standardised procedures instead improve reliability by reducing variation in how instructions and tasks are delivered."}]},{"id":"fd07f23f-b716-428f-8366-699c5c934bc7","cardType":"basic","points":1,"front":"Which participant effect occurs when cues make participants guess the aim and change behaviour?","back":"Demand characteristics.","mcqOptions":[{"text":"Demand characteristics.","correct":true,"explanation":"Demand characteristics occur when participants infer the study’s aim from cues and consciously or unconsciously alter their behaviour in response."},{"text":"Investigator effects.","correct":false,"explanation":"Investigator effects arise when a researcher’s behaviour or expectations influence the study. When participants guess the aim from cues and change behaviour, this is demand characteristics."},{"text":"Social desirability bias.","correct":false,"explanation":"Social desirability bias involves giving responses that appear socially acceptable. Behaviour changed because cues reveal the study’s aim is specifically caused by demand characteristics."},{"text":"Evaluation apprehension.","correct":false,"explanation":"Evaluation apprehension is anxiety about being judged during a study. Guessing the aim from cues and adjusting behaviour to fit or resist it describes demand characteristics."}]},{"id":"c2f0f623-cfac-4f16-a5cf-9741771734a6","cardType":"basic","points":1,"front":"What sample issue may make primary data lack generalisability?","back":"A small, biased or unrepresentative sample.","mcqOptions":[{"text":"A small, biased or unrepresentative sample.","correct":true,"explanation":"A small, biased or unrepresentative sample may not reflect the target population, so findings from the primary data cannot confidently be generalised more widely."},{"text":"A large, random and representative sample.","correct":false,"explanation":"A large, randomly selected and representative sample would generally improve generalisability. The problem arises when the sample is small, biased or unrepresentative."},{"text":"A stratified and proportionate sample.","correct":false,"explanation":"A properly stratified, proportionate sample should reflect important population groups and support generalisability. A small, biased or unrepresentative sample creates the actual problem."},{"text":"A randomly selected opportunity sample.","correct":false,"explanation":"An opportunity sample is chosen through availability rather than random selection, so this description combines incompatible sampling methods. The relevant issue is a small, biased or unrepresentative sample."}]},{"id":"2820f5df-60b6-4a07-b60b-c38e4d64c0d5","cardType":"basic","points":1,"front":"What is the main strength of secondary data?","back":"Efficiency - it uses information already collected.","mcqOptions":[{"text":"Efficiency - it uses information already collected.","correct":true,"explanation":"Secondary data already exists, so researchers can often access and analyse it more quickly and cheaply than collecting an entirely new set of primary data."},{"text":"Control - it lets researchers design every procedure.","correct":false,"explanation":"Researchers usually have limited control over how secondary data was originally gathered. Its main strength is efficiency because the information has already been collected."},{"text":"Specificity - it always matches the current research aim.","correct":false,"explanation":"Secondary data was usually gathered for another purpose, so it may not match the current aim. Its main strength is efficiency because it already exists."},{"text":"Accuracy - it guarantees error-free measurements.","correct":false,"explanation":"Previously collected data is not automatically accurate and may contain measurement or recording problems. Its principal advantage is efficiency, not guaranteed accuracy."}]},{"id":"c8019db2-5a2e-4f9e-8dd6-9f9f2043a403","cardType":"basic","points":2,"front":"Why use secondary data for childhood records from past decades?","back":"Researchers cannot go back in time to collect them.","mcqOptions":[{"text":"Researchers cannot go back in time to collect them.","correct":true,"explanation":"Historical childhood records describe events and experiences that have already occurred. Secondary data allows researchers to study them because new first-hand data cannot be collected retrospectively."},{"text":"Researchers can recreate past conditions exactly to collect them.","correct":false,"explanation":"Past social conditions and individual childhood experiences cannot be recreated exactly. Existing secondary records are needed because researchers cannot go back in time to collect the original data."},{"text":"Researchers need no permission from participants to collect them.","correct":false,"explanation":"Using old records can still require ethical approval, permission and consideration of consent. Their value is that researchers cannot go back in time to collect equivalent childhood data."},{"text":"Researchers can improve the original measures to collect them.","correct":false,"explanation":"Researchers analysing secondary records cannot alter how the original variables were measured. They use those records because the past data cannot now be collected first-hand."}]},{"id":"82c012a5-463f-4efe-8fcb-4f1030927a34","cardType":"basic","points":1,"front":"What is the biggest weakness of secondary data for a new study?","back":"It may not match the current aim.","mcqOptions":[{"text":"It may not match the current aim.","correct":true,"explanation":"Secondary data was collected for a different purpose, so its variables, measures or level of detail may not adequately address the new research aim."},{"text":"It may not produce quantitative data.","correct":false,"explanation":"Secondary sources can provide either quantitative or qualitative data, so data type is not the central problem. The main weakness is possible mismatch with the current aim."},{"text":"It may not have been gathered online.","correct":false,"explanation":"Whether information was collected online does not determine its usefulness as secondary data. The major concern is whether it matches the new study’s current aim."},{"text":"It may not involve a controlled experiment.","correct":false,"explanation":"Secondary data can originate from many methods and does not need to come from an experiment. Its biggest limitation is that it may not match the current aim."}]},{"id":"35724f7b-fc34-4f53-be84-bda86e36046f","cardType":"basic","points":1,"front":"What consent issue remains when using secondary data?","back":"Whether participants consented to data reuse.","mcqOptions":[{"text":"Whether participants consented to data reuse.","correct":true,"explanation":"Consent for the original study does not necessarily cover later analysis by different researchers. Researchers must consider whether participants agreed to their data being reused."},{"text":"Whether participants approved the new hypothesis.","correct":false,"explanation":"Participants do not need to approve a researcher’s hypothesis. The relevant consent question is whether their original agreement allowed their data to be reused."},{"text":"Whether participants agreed with the final findings.","correct":false,"explanation":"Participants are not required to agree with a study’s conclusions. The ethical issue is whether they consented to their previously collected data being reused."},{"text":"Whether participants selected the research method.","correct":false,"explanation":"Choosing the research method is the researcher’s responsibility, not a condition of participant consent. The key issue is whether consent covered later data reuse."}]},{"id":"e3b61305-c23e-4e14-b680-80466851a55b","cardType":"cloze","points":null,"front":"A meta-analysis [ ] findings from multiple studies to estimate an [ ].","back":"A meta-analysis statistically combines findings from multiple studies to estimate an overall pattern or effect.","mcqOptions":[{"text":"A meta-analysis statistically combines findings from multiple studies to estimate an overall pattern or effect.","correct":true,"explanation":"Meta-analysis applies statistical techniques to results from several studies, producing a combined estimate that reveals the overall pattern or magnitude of an effect."},{"text":"A meta-analysis qualitatively describes findings from multiple studies to estimate an individual participant’s score.","correct":false,"explanation":"This confuses meta-analysis with a narrative review and individual-level measurement. Meta-analysis statistically combines study findings to estimate an overall pattern or effect."},{"text":"A meta-analysis statistically separates findings from multiple studies to estimate an overall pattern or effect.","correct":false,"explanation":"Meta-analysis does not separate findings and consider them only in isolation. It statistically combines findings from multiple studies to estimate an overall pattern or effect."},{"text":"A meta-analysis statistically combines findings from multiple studies to estimate an unstandardised raw score.","correct":false,"explanation":"A raw score is tied to a particular measure and is not the aim of meta-analysis. The combined evidence estimates an overall pattern or effect."}]},{"id":"1038fb7d-19f1-4ed6-84fb-2eff1967a319","cardType":"basic","points":1,"front":"Why is meta-analysis a form of secondary data analysis?","back":"It uses results from completed studies.","mcqOptions":[{"text":"It uses results from completed studies.","correct":true,"explanation":"Secondary analysis uses information that already exists. Meta-analysis analyses results produced by completed studies rather than collecting new, first-hand data from participants."},{"text":"It collects new responses from participants.","correct":false,"explanation":"Collecting new responses would produce primary data. Meta-analysis is secondary analysis because it uses results that have already been generated by completed studies."},{"text":"It manipulates variables in new experiments.","correct":false,"explanation":"Manipulating variables in a new experiment is primary research. Meta-analysis instead analyses results from completed studies without conducting those original investigations again."},{"text":"It records new observations of behaviour.","correct":false,"explanation":"Recording new behavioural observations creates primary data. Meta-analysis qualifies as secondary analysis because its evidence comes from the results of completed studies."}]},{"id":"a9735fff-9849-43ef-b976-9b34c32882a0","cardType":"basic","points":1,"front":"What do inclusion criteria decide in a meta-analysis?","back":"Which studies are included.","mcqOptions":[{"text":"Which studies are included.","correct":true,"explanation":"Inclusion criteria specify the characteristics a study must have to enter the meta-analysis, ensuring that researchers select evidence systematically and consistently."},{"text":"Which studies are statistically significant.","correct":false,"explanation":"Selecting studies only because they have significant findings would create bias. Inclusion criteria determine which studies are included using predefined, relevant characteristics."},{"text":"Which participants are randomly allocated.","correct":false,"explanation":"Random allocation concerns assigning participants to conditions within an experiment. Inclusion criteria instead determine which entire studies are admitted to the meta-analysis."},{"text":"Which variables are experimentally manipulated.","correct":false,"explanation":"The researchers who conducted the original experiments decided which variables to manipulate. Meta-analysis inclusion criteria determine which completed studies are included."}]},{"id":"f39f3d50-8d1c-4501-8111-ed15a60cf8a9","cardType":"basic","points":1,"front":"What does an effect size help judge beyond statistical significance?","back":"The strength/size of a relationship or difference.","mcqOptions":[{"text":"The strength/size of a relationship or difference.","correct":true,"explanation":"An effect size indicates how large or strong an observed relationship or group difference is, adding information about practical importance beyond statistical significance."},{"text":"The probability/significance of a relationship or difference.","correct":false,"explanation":"This confuses effect size with a significance test or p-value. Effect size assesses the strength or size of a relationship or difference."},{"text":"The sample/number of participants in a study.","correct":false,"explanation":"Sample size counts participants and can affect statistical power, but it is not the effect size. Effect size judges the strength or size of a relationship or difference."},{"text":"The validity/reliability of a relationship or difference.","correct":false,"explanation":"Validity and reliability concern measurement quality and consistency, not the magnitude of a finding. Effect size judges the strength or size of a relationship or difference."}]},{"id":"1d65ab43-a57e-4057-ba49-eaee89bc9c2c","cardType":"basic","points":2,"front":"How does meta-analysis increase confidence in conclusions?","back":"It combines many studies, giving greater statistical power.","mcqOptions":[{"text":"It combines many studies, giving greater statistical power.","correct":true,"explanation":"Combining evidence from many studies effectively increases the amount of data considered, improving statistical power and confidence that a genuine effect can be detected."},{"text":"It combines many studies, giving greater ecological validity.","correct":false,"explanation":"Combining studies does not automatically make their tasks or settings more realistic. Confidence increases mainly because the larger combined evidence base provides greater statistical power."},{"text":"It combines many studies, giving greater experimental control.","correct":false,"explanation":"Meta-analysts cannot increase control over procedures used in completed studies. Combining their results increases confidence by providing greater statistical power."},{"text":"It combines many studies, giving greater observer reliability.","correct":false,"explanation":"Observer reliability concerns agreement between people recording behaviour and is not automatically improved by meta-analysis. Combining many studies primarily provides greater statistical power."}]},{"id":"e439f70d-5ee3-4d66-9d56-7ea81a3ba25e","cardType":"basic","points":2,"front":"What does “garbage in, garbage out” mean for meta-analysis?","back":"Weak original studies give weak combined conclusions.","mcqOptions":[{"text":"Weak original studies give weak combined conclusions.","correct":true,"explanation":"A meta-analysis cannot repair fundamental flaws in its source studies. If the original evidence is poor quality, the combined conclusion will also be weak."},{"text":"Weak original studies give strong combined conclusions.","correct":false,"explanation":"Combining several flawed studies does not cancel their methodological weaknesses. Weak original evidence produces weak combined conclusions, even when sophisticated statistical methods are used."},{"text":"Weak original studies give fully valid conclusions.","correct":false,"explanation":"Statistical combination cannot make biased, unreliable or poorly designed studies fully valid. Weak original studies lead to weak combined conclusions."},{"text":"Weak original studies give more objective conclusions.","correct":false,"explanation":"Objectivity is not guaranteed by pooling poor-quality evidence. Biases and design flaws remain influential, so weak original studies produce weak combined conclusions."}]},{"id":"75293b06-00b3-44ae-8697-5c9731111b91","cardType":"cloze","points":null,"front":"In publication bias, studies with [ ] are more likely to be published, causing meta-analyses to [ ].","back":"In publication bias, studies with significant or interesting findings are more likely to be published, causing meta-analyses to overestimate an effect.","mcqOptions":[{"text":"In publication bias, studies with significant or interesting findings are more likely to be published, causing meta-analyses to overestimate an effect.","correct":true,"explanation":"Journals preferentially publishing significant or striking results leaves null findings underrepresented. The available evidence therefore makes effects appear larger than they really are."},{"text":"In publication bias, studies with non-significant or null findings are more likely to be published, causing meta-analyses to underestimate an effect.","correct":false,"explanation":"This reverses the usual publication bias. Significant or interesting findings are more likely to appear in journals, so meta-analyses tend to overestimate the effect."},{"text":"In publication bias, studies with significant or interesting findings are more likely to be published, causing meta-analyses to prove cause and effect.","correct":false,"explanation":"Selective publication cannot establish causation. By hiding many null findings while favouring significant or interesting ones, publication bias causes meta-analyses to overestimate an effect."},{"text":"In publication bias, studies with large and representative samples are more likely to be published, causing meta-analyses to eliminate sampling error.","correct":false,"explanation":"Publication bias concerns selective publication of significant or interesting findings, not simply large samples. This selection can overestimate an effect, and sampling error is never completely eliminated."}]},{"id":"e8c71b45-4efb-49e4-8bd5-cea00b028e21","cardType":"cloze","points":null,"front":"If included studies differ in important ways, this is [ ], making it harder to [ ].","back":"If included studies differ in important ways, this is heterogeneity, making it harder to combine them meaningfully.","mcqOptions":[{"text":"If included studies differ in important ways, this is heterogeneity, making it harder to combine them meaningfully.","correct":true,"explanation":"Heterogeneity means the studies vary in important characteristics, such as methods, samples or measures. Such differences reduce how meaningfully their results can be combined."},{"text":"If included studies differ in important ways, this is homogeneity, making it harder to combine them meaningfully.","correct":false,"explanation":"Homogeneity means similarity rather than important variation and generally makes combination easier. Important differences between studies are heterogeneity, which makes meaningful combination harder."},{"text":"If included studies differ in important ways, this is sampling bias, making it harder to combine them meaningfully.","correct":false,"explanation":"Sampling bias occurs when a sample is systematically unrepresentative. Differences between included studies are called heterogeneity, and these differences make meaningful combination more difficult."},{"text":"If included studies differ in important ways, this is heterogeneity, making it harder to collect primary data.","correct":false,"explanation":"Heterogeneity does describe important differences between studies, but meta-analysis uses existing results rather than collecting primary data. The differences make the studies harder to combine meaningfully."}]}]}],"examCountdown":{"examDate":"2027-05-18","paperLabel":"Paper 1"},"heading":"Primary and secondary data","title":"Primary and secondary data Flashcards","topbar":{"backHref":"/a-level/psychology/aqa/flashcards"},"topicSidebar":"$L36"}]}],"topicId":"091859ca-4a3d-5968-9272-4c8ea1f47207","walled":"$L37"}],"$L38","$L39"]