Quizlet cards AQA research methods

• Study notes on A-level Psychology Research Methods (AQA)

Experimental Methods

• Manipulation of an independent variable (IV) to measure its effect on a dependent variable (DV).

Aim

• General statement of what the researcher intends to investigate; it outlines the study's purpose.

Hypothesis

• A statement made at the start of a study that describes the relationship between the variables being investigated.

Types of Hypothesis

• Directional: Specifies the direction of the relationship between two conditions.
• Non-directional: States a difference exists between conditions but doesn't specify the direction.

Independent Variable (IV)

• Variable that is changed or manipulated to affect the DV, allowing for measurement of its impact.

Dependent Variable (DV)

• Variable that is measured by the researcher; any effect observed should be caused by the IV.

Operationalisation

• Clearly defining variables in terms of how they can be measured in a study.

Extraneous Variables

• Variables other than the IV that may affect the DV, need to be identified and minimized.
• Don't systematically change with the IV.
• Example: Age of participants.

Confounding Variables

• Change systematically with the IV.
• Makes it difficult to determine whether changes in the DV are due to the IV or the confounding variable.

Demand Characteristics

• Cues from the researcher or the situation that participants interpret as revealing the study's purpose.
• Cause participants to change their behavior.

Investigator Effects

• Any effect of the investigator's behavior on the research outcome.

Randomisation

• Using chance methods to control for bias when designing materials and the order of conditions.

Standardisation

• Using the same formalized procedures and instructions for all participants in a study.

Independent Groups Design

• Two separate groups of participants experience two different conditions of the experiment.
• Strengths include no order effects and participants are less likely to guess the aim.
• Limitations include participant variables differ as different people are used, DV changes could be due to participant variables and is less economical

Repeated Measures Design

• Participants experience all conditions of the experiment.
• Strengths include controlled participant variables and if fewer participants are needed
• Limitations include order effects, participants improve with practice, more likely to guess the aim and demand characteristics.

Matched Pairs Design

• Participants are paired based on variables relevant to the study.
• One member of each pair does one condition.
• Strengths include no order effects and demand characteristics being less of a problem.
• Limitations include participants can never be matched or timed exactly, is time consuming and expensive

Counterbalancing

• An attempt to control order effects in a repeated measures design.
• Half participants take part in condition A then B and the other half take part in condition B then A.
• Can be referred to as ABBA technique

Random Allocation

• Participants should be randomly allocated to different experiment groups to address participant variables

Laboratory Experiments

• Conducted in highly controlled environments.
• Strengths include high control over confounding and extraneous variables, so high internal validity and easy replication.
• Limitations include lack of generalizability, artificial environment, lacks real-life application and demand characteristics.

Natural Experiments

• The change in IV is not brought about by the researcher but has no control over it.
• Strengths include greater mundane realism and high external validity.
• Limitations include loss of control over CV and EV, cause and effect is more difficult to establish and ethical issues as participants are unaware they are being studied.

Field Experiments

• Takes place in a natural everyday setting.
• Strengths include opportunities for research that wouldn't of happened for practical or ethical reasons, and high external validity.
• Limitations include rare occurrence and participants cannot be randomly allocated to experimental conditions.

Quasi-Experiments

• Lacks key ingredients of a true experiment, such as the IV being determined by anyone (e.g., age).
• Strengths include easy replication and high internal validity.
• Limitations include potential confounding variables.

Population

• The group of people who are the focus of the researcher's interest.

Sample

• A group of people who take part in a research investigation.
• Drawn from a population to be representative of it.

Random Sample

• All members of the target population have an equal chance of being selected.
• Involves obtaining a list of the population, assigning numbers, and using a lottery method.
• Strength includes potentially unbiased selection.
• Limitations include difficulty, time consumption, potential unrepresentativeness and participant refusal.

Systematic Sample

• Selecting every nth member of the target population.
• A sampling frame is produced.
• Strengths include objectivity and no influence over who is chosen.
• Limitations include time consumption and potential participant refusal.

Stratified Sample

• Subgroups within a population are represented proportionally in the sample.
• Involves identifying strata and working out the required proportions.
• Strengths include possible generalization of findings.
• Limitations include inability to reflect all ways people differ.

Opportunity Sample

• Selecting participants who are willing and available.
• Strengths include convenience, cost-effectiveness, and less time consumption.
• Limitations include bias, unrepresentative sample and potential researcher bias.

Volunteer Sample

• Participants select themselves to be part of the sample (self-selection).
• Strengths include ease and minimal input required, less time-consuming.
• Limitations include volunteer bias.

Ethical Issues

• Conflicts between participants' rights and researchers' needs to gain valuable findings.

Informed Consent

• Prospective participants should know what they are getting into before participating.
• Involves making participants aware of the research aims, procedures, rights, and data usage.

Dealing with Informed Consent

• Participants should be issued with a consent letter detailing relevant information that might affect their decision.

Deception

• Deliberately misleading or withholding information from participants at any stage.
• Justifiable if it doesn't cause distress.

Protection from Harm

• Participants should not experience anything beyond what's normally expected.

Dealing with Deception and Protection from Harm

• Provide a full debriefing, disclose true aims, ensure right to withdraw data.

Privacy and Confidentiality

• Participants have the right to control information about themselves.
• Confidentiality should be protected under the Data Protection Act.

Dealing with Confidentiality

• Protect personal details, use numbers/initials.
• Assure data protection during briefing and debriefing.

Pilot Studies

• A small-scale version of an investigation before the real one.
• Aims to check procedures, materials, etc., working and make modifications.

Single-Blind Procedure

• Participants are unaware of the research aim to reduce demand characteristics.

Double-Blind Procedure

• Neither participants nor researchers know the investigation's aims.
• Used in drug trials to prevent bias related to placebo effects.

Observation Techniques

• Way of seeing what people do without asking them.
• Can be naturalistic or controlled, covert or overt, participant or non-participant.

Naturalistic Observation

• Takes place in the setting where the target behavior usually occurs.
• Strengths include high external validity
• Limitations include difficulty replicating and uncontrolled confounding or extraneous variables

Controlled Observations

• Researcher controls aspects of the research situation.
• Strengths include easier replication.
• Limitations include difficult application to everyday life

Covert Observations

• Participants are unaware they are being observed.
• Strengths include removes demand characteristics and increase internal validity.
• Limitations include ethical concerns due to lack of consent.

Overt Observations

• Participants know they are being observed and have given informed consent.
• Strengths include being more ethically acceptable.
• Limitations include potential for demand characteristics.

Participant Observations

• Observer becomes part of the group they are studying.
• Strengths include high internal validity
• Limitations include potential loss of objectivity.

Non-Participant Observations

• Researchers remain separate and record behavior objectively.
• Strengths include maintained objectivity.
• Limitations include loss of valuable insights due to distance.

Observational Design

• Can be structured or unstructured.
• Involves behavior categories and sampling methods..

Structured Observation

• Uses behavior categories to simplify target behaviors, suited for large-scale observations.
• Strengths include easier and more systematic data recording.
• Limitations include potential omission of useful or important behaviors.

Unstructured Observation

• Records everything seen and appropriate in small-scale detailed observations.
• Strengths include detailed information.
• Limitations include the risk of observer bias and difficulty in data analysis.

Behaviour Categories

• Breaking up target behaviors into observable, measurable components (operationalisation).
• Strengths include structured and objective data.
• Limitations include the categories should be exclusive and not overlap

Sampling Methods

• Two categories: event sampling and time sampling
• Event Sampling: Recording an event each time it occurs.
• Strengths include it's useful when behavior is infrequent or could be missed
• Limitations include if too complex may overlook important details and could be unrepresented as a whole
• Time Sampling: Recording behavior within pre-established time frame.
• Strengths include effectively reduces the number of observations.
• Limitations include it may be unrepresented as a whole

Self-Report Techniques

• Three categories: Questionnaires, structured and unstructured interviews

Questionnaires

• Pre-set list of written questions participants respond to.
• Used to assess thoughts and/or feelings.
• Can be used to assess the dependent variable.

Open Questions

• Do not have fixed responses.
• Respondents answer freely.

Closed Questions

• Offer fixed number of responses.
• Usually a yes or no format.

Questionnaire Evaluation

• Strengths include cost-effective, quick data gathering and straightforward analysis.
• Limitations include responses may not be useful, potential for demand characteristics, often produces response bias.

Interviews

• Face-to-face interaction between an interviewer and interviewee.

Structured Interview

• Predetermined questions in a fixed order.
• Strengths include easy replication.
• Limitations include limits data as can't explain the question

Unstructured Interview

• No set questions.
• General aim topic is discussed and it is free flowing.
• Strengths include flexibility.
• Limitations include interviewer bias.

Semi-structured Interview

• Has a list of questions.
• Interviewers can ask follow-up questions based previous answers.

Self-Report Designs: Designing Questionnaires

• Likert scale (agreement on a scale).
• Rating scale (strength of feeling).
• Fixed choice option (selecting applicable options).

Self-Report Designs: Designing Interviews

• Use an interview schedule (list of questions to ask).
• Schedule should be standardized to reduce interviewer bias.

Writing Good Questions

• Clarity is essential.
• Avoid jargon.
• Use neutral alternatives for emotive language and avoid leading questions.
• Avoid double-barreled questions and double negatives.

Correlations

• Illustrates the strength and direction of association between two or more co-variables.
• Plotted on scatter graphs.
• Strengths include provides precise and quantifiable measure, good starting point, doesn't need manipulation is less time consuming
• Limitations include only tells us relationship but not why or can't be cause and effect, could be intervening variable can be misused or misinterpreted

Positive Correlation

• Both co-variables increase together.

Negative Correlation

• As one co-variable increases, the other decreases.

Zero Correlation

• No relationship between co-variables.

Difference Between Correlations and Experiments

• Experiments: Researcher controls/manipulates the IV to measure effects on the DV.
• Correlations: No manipulation and cannot establish cause and effect.

Types of Data

• Quantitative, qualitative, primary, and secondary.

Qualitative Data

• Expressed in words rather than numbers.
• Written descriptions of thoughts or feelings.
• Strengths include it offer details and know other's opinions or feelings, external validity
• Limitations include it's difficult to analyse and it's subjective to bias

Quantitative Data

• Expressed numerically.
• Numerical data in the form of individual scores.
• Strengths include simple to analyse, more objective and less bias.
• Limitations include narrow meaning detail, fails to represent 'real life'

Primary Data

• Original data collected for the specific purpose of the investigation.
• Strengths include it fits the job for the purpose of investigation
• Limitations include requires time and effort

Secondary Data

• Data collected by someone other than the researcher.
• Already exists and easy to access data.
• Strengths include inexpensive and can find other info
• Limitations include quality and accuracy are a concern, may be outdated or incomplete

Measures of Central Tendency

• Averages (mean, median, mode).

Mean

• Add all values and divide by the total number of scores.
• Strengths include sensitive nature that includes all values so representative of the data
• Limitations include easily distorted by extreme values.

Median

• Middle value in a data set when scores are arranged lowest to highest.
• Strengths include it's not affected by extreme scores, easy to calculate
• Limitations include less sensitive if lowest and highest numbers are ignored

Mode

• Most frequent score/value in the data set.
• Strengths include easy to calculate, can only use mode when using opinions
• Limitations include crude measure and not useful if several modes.

Measures of Dispersion

• Based on the spread of scores (range, standard deviation).

Range

• Highest value minus the lowest value, plus 1.
• Strengths include easy to calculate
• Limitations include outliers affect result and is unrepresentative as a whole

Standard Deviation

• How far scores deviate from the mean.
• High SD = greater spread.
• Low SD = tightly clustered data.
• Strengths include more precise than range
• Limitations include affected by outlier

Presentation of Quantitative Data

• Tables, bar graphs (categories), histograms (continuous data), scatter graphs (co-variables).

Normal Distribution

• Frequency measurements form a bell-shaped curve.

Skewed Distribution

• Leans to one side.
• Positive skew leans left and mode remains the highest, then median, then mean
• Negative skew leans in the opposite direction.

Concept of Significance

• Determines if a hypothesis should be accepted or rejected.

Sign Test

• Used to determine significance.
• Look at difference, use repeated measures, need nominal data.

How to do a Sign Test

• Convert data to nominal data and put in table.
• Do + and - for differences and total the + and -.
• Less frequent sign is S.
• Compare calculated S value with critical value.

Critical Value

• S is compared to the critical value for significance.
• Need significance level, number of participants, directional or non-directional hypothesis.

Concept of Probability (P)

• Likelihood of a certain event.
• Accepted level in psychology is 0.05/5%.

Peer Review

• All written investigations are scrutinized by a small group of experts in the same field.

Main Aims of Peer Review

• Allocate funding for research findings.
• Validate the quality and relevance of research.
• Suggest amendments or improvements.

Evaluation of Peer Review

• Anonymity to remain honest appraisal
• Publication bias for publishing good findings.
• Groundbreaking research to suppress opposition mainstream theories.