Component 2: definitions Flashcards
Independent variable
The variable manipulated by the researcher to investigate whether it brings about a change in the dependent variable
Dependent variable
The variable the researcher measures but does not manipulate in an experiment
Operationalisation
The process of making variables measurable
Standardisation
A set of procedures or instructions that are kept the same
Random allocation
Allocating participants to experimental groups using random techniques
Experimental condition
Refers to the group of participants who are exposed to the independent variable
Control condition
Lacks any treatment or manipulation of the independent variable
Extraneous variable
Not measured or manipulated by the researcher, affects results of all participants equally, might impact the DV if not well controlled
Extraneous variable examples
Gender, age, temperature, noise volume, weather, location, experimenter
Confounding variable
Damages the results, anything the researcher is not aware of or cannot control
Confounding variable examples
Mood, amount of sleep, competitiveness, personality
Aim
A general statement describing the purpose of an investigation
Hypothesis
A testable statement that can be proven or disproven
Directional hypothesis
A testable statement based on previous research, findings predict the direction of results between conditions
Key terms: directional hypothesis
More/less, increase/decrease, higher/lower
Non-directional hypothesis
A testable statement with no previous research findings or conflicting research, predicts an effect not a direction
Key terms: non-directional hypothesis
Difference or effect
Null hypothesis
There is no difference or effect between the variables, any differences are due to chance factors
Locations of research
Laboratory, field, online
Lab location
Artificial environment, participants know they are being studied, maximum control of variables
Demand characteristics
Participants aware they are being studied, they change their behaviour as a result, it is unknown whether the behaviour they display is real or true
Field location
Less controlled than lab, natural environment, everyday location,
Online location
Faster to find larger, global group of participants
Mundane realism
The extent to which a study reflects a real life environment
Ecological validity
The extent to which findings of the study can be applied to the real world
(environment)
Types of experiment
Laboratory, field, natural, quasi
Quasi experiment
No deliberate manipulation of the IV, no random allocation of participants to experimental groups, IV is a naturally occurring difference, often an innate characteristic, DV measured in a lab
Lab experiment
Controlled and artificial setting, contains both experimental and control conditions, random allocation, IV and DV
Natural experiment
Research does not deliberately manipulate IV - it occurs naturally, DV is tested in a lab, field or online
Field experiment
Participants unaware they are being researched, IV and DV
Lab location: advantages and disadvantages
Control over extraneous and confounding variables, easier replication of research, high demand characteristics
Field location: advantages and disadvantages
Lower demand characteristics = more natural behaviour, high ecological validity and mundane realism, difficult to control confounding and extraneous variables, lab equipment may be difficult to transport
Online location: advantages and disadvantages
Access to a diverse and larger group of participants, cost effective and fast, methods are limited = surveys or questionnaires, ethical issues = consent and protection of participants
Name the three types of experimental design
Independent measures, repeated measures, matched pairs
Independent measures
Participants take part in only one condition
How many groups of participants are there in a independent measures design?
Two seperate groups
Repeated measures
Participants take part in all conditions of the experiment
How many groups of participants are there in a repeated measures design?
One group
Matched pairs
Participants are matched in each condition for their characteristics, may have an effect on their performance, each participant takes part in one condition
How are participants matched in a matched pairs design?
One for one (in pairs), by having the same characteristic as their pair, but each participant takes part in one condition
Name the three types of order effects
Practice, fatigue, boredom
What are the advantages of an independent measures design?
No order effects, demand characteristics are less of a problem
What are the disadvantages of an independent measures design?
Individual differences (participant variables) are an issue
What are the advantages of a repeated measures design?
Eliminates participant variables
What are the disadvantages of a repeated measures design?
Order effects may be present, greater chance of demand characteristics
What are the advantages of a matched pairs design?
No order effects, controls participant variables (individual differences)
What are the disadvantages of a matched pairs design?
Time consuming and difficult to get right
How can individual differences in an independent measures design be controlled?
Random allocation
How can order effects in a repeated measures design be controlled?
Counterbalancing
What is counterbalancing?
ABBA: half of the group does condition one then two, the other half does condition two then one
How can participant variables be further minimised in a matched pairs design?
Identical twins
Name the seven sampling techniques
Opportunity, self-selected, random, systematic, stratified, quota, snowball
What is the target population?
The larger group from which the sample is drawn
What is a sampling frame?
A list of all members of the target population
Describe opportunity sampling
People are chosen who are available at the time of study and fit the criteria
Describe self-selected sampling
People put themselves forward for a study, respond to advert on social media
Describe random sampling
Everyone has an equal chance of getting selected (e.g. random number generator), list of target population needed
Describe systematic sampling
Every nth person is selected (fixed intervals), list of target population needed
Describe stratified sampling
Random based, representitive of population = random selection and the sample represents the demographics of the population
Describe quota sampling
Opportunity based, representitive of population = researcher chooses participants and gets set quota from each category of the population
Describe snowball smapling
Initial contact used to provide further contacts, usually used when target population is not easy to accessd
Strengths of opportunity sampling
Convenient + quick to carry out, economical
Weaknesses of opportunity sampling
Biased (those chosen are those who look approachable), not representitive (similar kinds of people), selective (small group of target population
Strengths of self-selected sampling
Ethical, not very time consuming (participants approach researcher)
Weaknesses of self-selected sampling
Respondents are open to demand characteristics, not representitive (specific type of person)
Strengths of random sampling
Sample selected in unbiased way (everyone has equal chance of getting selected)
Weaknesses of random sampling
Time consuming to create list of people if large population, not neccessarily most representitive way, may select one type of person
Strengths of systematic sampling
Unbiased as objective, quick to carry out once frame created
Weaknesses of systematic sampling
Not everyone has equal chance of being included, not truly random or representitive
Strengths of stratified sampling
Equal representation of all groups, everyone in each category has equal chance in being selected
Weaknesses of stratified sampling
Difficult to identify sub-categories, requires organisation = time consuming
Strengths of quota sampling
Equal representation of all groups, quicker as participants selected from each group conveniently (opportunity based)
Weaknesses of quota sampling
Requires organisation = time consuming, may be biased as sample not random (opportunity based)
Strengths of snowball sampling
No sampling frame required, may give access to groups difficult to access (e.g. deviant groups)
Weaknesses of snowball sampling
Time consuming, not random = may not be representitive, may run out of new contacts
Name the ethical issues
Privacy, Confidentiality, Deception, Right to withdraw, Informed consent, Protection from harm (PC DRIP)
