research methods year 1 Flashcards
explain what is meant by an ‘aim’
general statement which describes the purpose of an investigation
explain what is meant by a hypothesis
statement which is made at the start of a study and clearly describes the relationship between the variables
explain what is meant by an IV
independent variable
the factor that changes
explain what is meant by a DV
dependent variable
factor that is being measured
explain what is meant by operationalisation
ensuring the variables are measurable
explain the difference between a directional hypothesis and a non-directional hypothesis
a directional hypothesis shows the expected difference between the two variables which is anticipated
(often used when there is previous research/theories suggesting a specific outcome)
a non-directional hypothesis demonstrates there is a link between the variables expected but does not state the nature of this difference
(often used when there is little previous research/the research is contradictory)
what are confounding variables?
a type of extraneous variable which differs systematically with the independent variable
what is an extraneous variable?
a variable which is not being investigated in the study which has the potential to affect the outcome
what are demand characteristics?
characteristics as a result of the participants trying to make sense of the study and act accordingly to support the aim of the research
explain what is meant by investigator effects
any unwanted influence of the researcher on the research outcome
explain what is meant by randomisation
use of chance methods to reduce researcher’s unconscious bias
minimises CVs and EVs
explain what is meant by standardisation
participants should be subject to same environment/information/experience
all procedures are standardised
explain ‘independent group design’
two separate groups of participants experience two separate conditions in the experiment
(often a control condition group and an experimental condition group)
explain ‘repeated measures’
all participants experience both conditions (often including a control condition)
results can be compared
explain ‘matched pairs’
participants are paired together based on a variable relevant to the experiment
(eg IQ or memory test)
pros and cons of laboratory experiment
+ high controls over variables (CV and EV)
+ replication possible - ensures validity
- lack generalisability, artificial environment may change natural behaviour
- low mundane realism
pros and cons of field experiments
+ high mundane realism, natural behaviour
+high external validity (may be unaware they’re being studied)
-loss of control of CVs and EVs
-lack of precision
-ethical issues (lack of consent?)
pros and cons of natural experiments
+ provide opportunity for research which may not have been done due to practical/ethical reasons
+ high external validity
-naturally occurring event doesn’t happen often- not a lot of opportunity for research
- participants may not be randomly allocated to experimental conditions
pros and cons of quasi experiments
+ controlled conditions, replication possible
- can not randomly allocate participants to conditions, may be confounding variables
describe a laboratory experiment set up
highly controlled conditions, in a lab or classroom
describe a field experiment set up
takes place in a natural everyday setting
describe a natural experiment set up
a natural event, researcher has no control over IV
describe a quasi experiment set up
IV is based on pre-existing differences between people (gender/age)
explain ‘random sampling’ and pros/cons
all members of the target population have an equal opportunity of being selected (lottery method)
+unbiased
+variables equally divided between groups
-time consuming
-difficult to obtain population list
explain ‘systematic sampling’ and pros/cons
every nth number of target population is selected and sampling frame is produced
+objective once frame is produced, researcher has no influence
-time consuming
-refusal can mean it is not representative
explain ‘stratified sampling’ and pros/cons
composition of sample represents proportions of people in certain subgroups.
the different ‘strata’ which make up a population are identified
+produces representative sample
-identified strata can no represent entire population
explain ‘opportunity sampling’ and pros/cons
takes a chance of whoever is around
+cheaper and quicker
- unrepresentative
-researcher controls who they select- bias