IB Psychology Flashcards
Define quantitative research (2)
quantifies collection + analysis of data
uses numbers + statistics
Examples of quantitative research (4)
Lab Experiments
Field Experiments
Quasi Experiments
Correlational Studies
Define qualitative research (3)
going beyond what can be quantified and measured + more subjective
asks “how” and “why” questions
data comes in form of texts
Examples of qualitative research (3)
Naturalistic Observation
Interviews
Case Studies
Define the aim in an experiment
sets out what the research wants to find out
Define the hypothesis in an experiment (2)
precise testable statement which can be right or wrong
idea/explanation based on existing evidence
Define operationalization (2)
specifically defining how a concept or variable will be measured/observed in a study
expressing something in terms of observable behaviour
Define the independent variable (2)
factor manipulated by the researcher - cause
what is changed
Define the dependent variable (2)
factor measured by the researcher
effect
Define a null hypothesis (2)
predicts no effect
manipulated variable will not cause a change in measured variable
Define an alternative hypothesis/research hypothesis (2)
predicts an effect
manipulated variable will cause some change in measured variable
Define a one-tailed hypothesis (2)
predicts an effect in one direction
one manipulated variable will produce an effect grater than another manipulated variable
Define a two-tailed hypothesis (2)
predicts an effect in either direction
manipulated variable will produce an effect greater or less than another manipulated variable
Define a confounding variable (2)
outside influence that effects the independent + dependent variables
type of extraneous variable
Define an extraneous variable
any variable other than IV that can affect the DV of the experiment
Features of a Lab Experiment (2)
controlled environment
researcher manipulates independent variable(s) to observe effect (dependent variables)
Features of a field experiment (2)
conducted in natural setting/real-world environment
researcher manipulates independent variable(s) to observe effect (dependent variables)
Features of Quasi experiments (2)
participants are grouped in pre-existing characteristics (age, gender) which act as IVs
IV not controlled by researcher
Features of Natural experiments
involves pre-existing IVs manipulated naturally
Pros of a lab experiment (2)
can establish cause and effect
high control
Negatives of a lab experiment
artificial setting - not reliable in real world
Pros of field experiment
natural setting - reliable in real world
Negatives of field experiment (2)
less control
possible ethical issues
Pros of natural experiment (2)
reliable in real world
ethically feasible
Cons of natural experiment (2)
no control over variables
difficult to replicate since unique
Pros of quasi-experiment (2)
practical
ethical
Cons of quasi-experiment (2)
confounding variables
less certain for cause
Features of Independent measures experiment design (2)
different participant used in different conditions of experiment
participants picked at random
Pros of independent measures experiment design (2)
avoids order effects
participants less likely to guess aim of experiment
Cons of independent measures design (2)
more participants required
one condition may not have equal quality participants to others
Features of Repeated measures experiment design
same participants take place in both conditions of experiment
Pros of repeated measures experiment design
fewer participants required
Cons of repeated measures experiment design
order effect - order of condition may affect participants behaviour + change results
Features of matched pairs experiment design (2)
pairs of participants matched in key variables (e.g age)
each member of pair separated into different conditions
Pros of matched pairs experiment design (2)
reduces participant variables
avoids order effects
Cons of matched pairs experiment design (2)
time-consuming to match pairs
impossible to match people exactly
Features of random sampling
every member of target population has equal chance of selection
Pros of random sampling (2)
minimizes bias - completely random + researcher has no control
most likely to produce representative sample of target pop.
Cons of random sampling (2)
time consuming + difficult to make list of target population
chance of obtaining unrepresentative sample
Features of opportunity sampling
selecting participants readily available to researcher
Pros of opportunity sampling
convenient + cost-effective - less time + effort
Cons of opportunity sampling (2)
likely to only represent small group rather than target pop.
researcher bias - researcher has control over selection
Features of stratified sampling
reflects proportion of different groups within target population
Pros of stratified sampling (2)
more representation
reduces researcher bias
Cons of stratified sampling
may not fully be representative
Features of volunteer sampling
participants choose themselves to be part of the study
Pros of volunteer sampling (2)
easy to conduct
diverse participants
Cons of volunteer sampling
may not be fully representative - participants may all share a characteristic
Features of systematic sampling
selecting participants from a larger population at regular intervals
Pros of systematic sampling (3)
easy + simple
reduces bias
even distribution
Cons of systematic sampling (2)
less random than random sampling
requires complete list of population
Pros of snowball sampling (3)
useful for hard to reach groups (e.g specific social groups)
efficient
good for qualitative research for in-depth sample
Features of snowball sampling
uses existing participants to recruit more participants among their acquaintances
Cons of snowball sampling (4)
may have bias - participants may recruit people with similar characteristics to them
lack of representation
dependent on network of participants
privacy concerns
Define demand characteristics
clues in an experiment that convey to the participants the purpose of the research
Define briefing
context/aim of experiment provided to participants after which participants will give consent
Examples of extraneous variables (6)
order effects
demand characteristics
investigator effects
participant variability
researcher bias
environment
Define participant variability
when characteristics of a sample affect the dependent variable
Examples of demand characteristics (3)
Expectancy effect
Screw you effect
social desirability effect
Define expectancy effect
participant attempts to give “right answer” to help prove researcher’s hypothesis
Define screw you effect
participant attempts to discern the hypotheses to destroy the credibility of the study
Define social desirability effect
participant answers to make themself look good to researcher
Define single blind (2)
participant does not know which condition of experiment they are in
reduces demand characteristics
Define double blind (2)
participant + researcher do not know which condition the participant is in
reduces demand characteristics + researcher bias
Define standardisation as a control variable
standardised procedure to prevent different instructions being read out
Define counterbalancing as a control variable (2)
used in repeated measures design
alternating the order which participants do experiments
Define reliability
consistent results
What does internal validity measure
how consistent the results are within themselves
What does external validity measure
how consistent the results are over time
Define validity
how accurately results satisfy the aim of experiment
What is meant by internal validity (2)
researchers have measured what they initially wanted to measure
have not been confounded by other variables e.g demand characteristics
What is meant by external validity
extent which study can be generalised/applied to other situations
Types of internal validity
construct validity
Define construct validity
how accurately a test measures an underlying principle
Types of external validity (2)
ecological validity
population validity
Parts of ethics in psychology (6)
consent
deception
confidentiality
debriefing
withdrawal
protection
Consent in ethics (2)
participants agreement should be based on full knowledge of experiment
can potentially influence validity of experiment by giving information
Deception in ethics
lying/withholding information to participants should be avoided when possible
Withdrawal in ethics
participant can leave and take data with them
Protection in ethics (2)
participants should not suffer due to experiment
researchers may not always be able to predict what happens but should intervene
Privacy in ethics
participants have rights to not be under scrutiny
Confidentiality in ethics
personal details of participants should be concealed
