Research Methods Flashcards by Lily Griffin

Experiments

Lab experiments

Definition - type of experiment conducted in a highly controlled setting where the researcher has control over all variables

Strength - high control over extraneous variables so there is high internal validity, replicable so there is high reliability

Weakness - low ecological validity as results in a lab may not accurately reflect real life settings, may cause unnatural responses, lacks mundane realism

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Experiments

Field experiments

Definition - type of experiment conducted in a real life setting where researcher manipulates IV and records DV

Strength - high ecological validity meaning results are more realistic and authentic, natural responses

Weakness - less control over extraneous variables, harder to establish a cause and effect relationship lowering internal validity, precise replication is difficult lowering reliability

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Experiments

Natural experiments

Definition - type of experiment conducted in a real life setting where someone or something else causes the IV to vary (eg before vs after a natural disaster) researcher records DV

Strength - high ecological validity, natural responses

Weakness - less control over extraneous variables meaning it is hard to generalise findings, low replicability resulting in low reliability

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Experiments

Quasi experiments

Definition - type of experiment in a real life or lab setting where the IV is something that already exists (eg memory in old vs young people)

Strength - usually carried out in a lab so high internal validity, due to trustworthy cause and effect

Weakness - low ecological validity as results in a lab may not accurately reflect real life settings, may cause unnatural responses, lacks mundane realism

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Experiments

Ethical issues

Informed consent - participants must willingly agree to participate once they know all aspects of the research

Right to withdraw - participants should be able to leave the study at any time under no conditions

Deception - researchers must not withhold information or mislead participants in any way and they must be aware of the true aims of the experiment

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Experiments

Ethical issues

Do no harm - researchers must protect participants from any physical or mental harm greater than that in everyday life

Confidentiality/privacy - any information about a participant in the study should be kept private unless previously agreed upon

Debrief - (after experiment) researcher should discuss the experience of the study once completed

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Experiments

Opportunity sampling

Definition - when the researcher asks whoever is available at the time of the study

Strength - convenient, cheap, not time consuming

Weakness- researcher bias (as researchers pick the participants)

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Experiments

Volunteer sampling

Definition - participants selecting themselves to be a part of the sample —> self selection

Strength - minimal effort from researcher and most engaged participants

Weakness - participants bias as only the most helpful people take part
—> findings cant be generalised

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Experiments

Random sampling

Definition - sample is collected through a lottery method (computer, phone, hat) so every member of the target population has an equal chance to be picked

Strength - potentially unbiased

Weakness - time consuming ti get a whole population, sample may refuse to take part

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Experiments

Systematic sampling

Definition - when every nth member of the target population is chosen to take part in the study

Strength - objective method - the researcher has no confirm over who is selected

Weakness - time consuming, participants may refuse to take part

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Experiments

Stratified sample

Definition- researcher identifies subgroups in the target population, then selects participants using random sampling to reflect the proportions in the population

Strength - most representative sample so can generalise finding to a target population

Weakness - time consuming, complete representation is near impossible

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Experiments

Features of science

Theory = system of ideas that can explain aspects on human thoughts, behaviour and emotion

Hypothesis = precise, testable statement of what researchers predict will be the outcome of a study

Objectivity = lack of researcher bias in opinion of judgement

Replicability = the study should obtain the same results if repeated exactly by the same/ different researcher

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Experiments

Features of science

Falsifiability = ability for a statement to be prove false

Paradigms = set of assumptions that create a viewpoint of the world

Paradigm shift = when there is a major change in approach/ dominant theory backed by new findings/ understanding

Empirical method = gathering information through direct observation for experience

Peer review = articles submitted for publication peer reviews

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Experiments

Types of hypotheses

Null hypothesis = suggests no effect “there will be no difference between (IV1) and (IV2) on (DV)

Directional hypothesis = predicts direction of the effect, used when there is prior research to suggest the effect
“(IV1) will (direction) on (DV) compared to (IV2)

Non directional hypothesis =doesn’t predict the direction of the effect
“There will be a significant difference between (IV1) and (IV2) on (DV)”

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Experiments

Aims, hypothesis and variables

Aim = general purpose of the investigation

Hypothesis = prediction that is specific on the outcome of a study Objectivity

Independent variable = manipulators by the researcher

Dependant variable = measured by the researcher

Experimental vs control condition = experimental group receives the treatment, control does not

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Experiments

Research issues - extraneous variables

Extraneous variables = any variable other than the independent variable that may have an effect on the dependant variable of not controlled

Experiments

Research issues - confounding variables

Confounding variables = type of extraneous variables but confounding variables vary systematically with the IV, creating a. Secondary IV

Experiments

Research issues - participant variables

Participant variables = anything about the person that might influence results

E.g. age, ability, mood, background, places to be, IQ, prejudice

How to control:
- match participants in different condition on certain characteristics such as age, culture, physical ability

Experiments

Research issues - situational variables

Situational variables = features of a situation that may influence participants behaviour

E.g order effects, heat, time of day

Order effects = how a person experiences conditions of the of the experiment

How to control:
Standardise = keep every thing the same for each participant

Experiments

Research issues - demand characteristics

Demand characteristic = in an experiment participants often actively look for clues as to how they should behave in that situation. If a person guesses/ knows the experiments intention they may change their behaviour accordingly

How to control:
— single blind = participant in unaware of experiments aims so prevents participants’ seeking clues
—deception = lying about aims of the study and/ or using distractions

Experiments

Research issues - investigator effects

Investigator effects = any unwanted influence of the investigator on research outcome - can be unconscious

E.g selection of participants, material of instructions

How to control:
— double blind = participant + researcher are unaware of the aims of the experiment
— randomisation = use of chance methods to avoid unconscious bias

Experiments

Experimental designs — Independent groups

Independent groups = two different conditions of the IV and participants experience only use one condition

Issue = participant variables

Resolution = randomly allocate participants to conditions A or B in hope that differences will be spread across the conditions

Experiments

Experimental designs —
Repeated measures

Repeated measures = all participants experience both conditions of the IV

issue = order effects

Resolution = counterbalancing (half the group do conditions A-B and the other half do B-A)
Or
= deceive participants to stop them guessing the purpose (single blind)

Experiments

Experimental designs —
Matched pairs

Matched pairs = participants are matched on a relevant variable then one goes to condition A and one to condition B

Issue = can’t match pairs in all variables

Resolution = match participant on as many variables as possible

Experiments Measures of central tendency ( finding a central point)

Mean = adding all number and dividing by the number of numbers Strength = takes all numbers into account Weakness = easily affected by anomalies Median = mid point of numbers once in order Strength = not affected by anomalies Weakness = doesn’t account for all data Mode = most frequently occurring number Strength = not affected by extreme values Weakness = doesn’t account for all values

Experiments Measures of dispersion (Shows the spread of data)

Range = difference between the highest and lowest values Strength = takes into consideration extreme scores Weakness = doesn’t measure the spread of the majority of all values Standard deviation = the mean distance of scores from the mean Strength = takes every score into account Weakness = time consuming Large SD = inconsistent scores Small SD = consistent scores

Experiments Types of data

Quantitative = numerical objective data E.g amount of yes/no answers, rating scale Qualitative = non-numerical subjective data E E.g words or opinions, pictures Primary data = first hand data gathered by the researcher themselves directly from participants for the purpose of their experiment Secondary data = any data set collected by any other person than the one using it

Experiments Strength and weaknesses of quantitative data

Strengths = can be analysed statistically so converted to graphs or charts, easy to compare with other data Weaknesses = lack of in depth detail, no meaningful insight into participants’ views, as participants can’t develop their opinions the results have low external validity

Experiments Strength and weaknesses of qualitative data

Strengths: rich in depth data, more meaningful insight into participants’ views, participants can be further develop their opinions Weaknesses: difficult to analyse and compare with other data, researcher bias presented as conclusions rely on subjective interpretations of the researcher

Experiments Strength and weaknesses of primary data

Strengths: targets the exact information which the researcher needs so the data fits their aims and objectives Weaknesses: requires time and effort, can be expensive

Experiments Strength and weaknesses of secondary data

Strengths = inexpensive, data is accessed so requires minimal effort to collect Weakness = may be likely that the data is outdated o incomplete, the data may not be reliable as the researcher was not present when conducted

Experiments Types of validity

Internal = the extent to which a research study establishes a trustworthy cause and effect relationship External = how well the outcome of a research study can be expected to apply to other settings Concurrent = the degree to which a test corresponds to an external criteria (how similar results are to an existing test)

Experiments Types of validity

Face = whether a test measure what its supposed to judged by an expert Ecological = a measure of how test performance predicts behaviours in real world settings Temporal = the extents to which findings are generalisable to other historical times Population = whether you can generalisable findings to a larger group of people Validity = the extent to which a test measures what if claims to measure

Experiments Types of Reliability

Reliability = how consistent something is Examples: Quantitative data, lab studies, questionnaires, observations with set categories

Experiments How to assess reliability

Test retests reliability = give the same test twice over a period of time to a group of people. Score from time 1 and time 2 can be controlled in order to evaluate the test for stability over time Inter rater reliability = degree of agreement among raters. It gives a score of how much consensus there is in the ratings given by judges. Should find a strong positive correlation between scores

Experiments Pilot studies

Pilot studies = small scale trial run of an experiment to test procedures, materials and instructions Used to identify: - unclear instructions - test equipment or materials - check timing and understanding DOES NOT CHECK FOR RESULTS - saves the researcher time and money before running the experiment