AS Level Flashcards
Operationalised hypothesis
Clearly defined and measurable statement
Directional hypothesis
States whether changes are greater or lesser, positive or negative
Non-directional hypothesis
Doesn’t state the direction, just that there’s a difference or correlation
When is a non-directional hypothesis used?
When there’s no theory or previous research
Research issues: Extraneous Variables
Are nuisance variables that have the potential to affect the results and may make it difficult to detect an effect.
A researcher may control these
:Research Issues: Confounding variables
Change systematically with the IV so we can’t be sure if any observed change in the DV is due to the CV or IV.
Research Issues: Demand characteristics
Any cue from the researcher or research situation that may reveal the aim of the study and change participants’ behaviour
Research issues: Investigator effects
Any effect if the investigator’s behaviour on the outcome of the research (the DV) and also on design decisions
Research issues: Randomisation
The use of chance when designing investigations to control for the effects of bias
Research issues: Standardisation
Using the same formalised procedures for all participants in a research study.
Differences become EVs otherwise
Pilot studies & more: Pilot Studies
Small scale trial run of an investigation to pre-test procedures so that research design can be modified if required
Pilot studies aren’t restricted just to experimental studies
Pilot studies & more: Single Blind Procedure
Participants don’t know the aims of the study so demand characteristics are reduced
Pilot studies & more: Double-blind procedure
Both the participant and the researcher don’t know the aims of the study to reduce demand characteristics
Pilot studies & more: Control groups and conditions
Control groups (independent measures) or control conditions (repeated measures) are used to set up a comparison.
They act as a baseline and help establish causation
Experimental designs: independent groups
One group does condition A and a second group does condition B.
Participants should be randomly allocated to experimental groups.
Independent groups: Positives + explanations
-No order effects: participants are only tested once so can’t practise or become bored/tired. This controls an important CV
-Won’t guess the aim: participants are only tested once so are unlikely to guess the aims. Therefore, behaviour may be more natural (higher realism)
Independent groups: Negatives + Explanations
-Participant Variables: the participants in the two groups are different, acting as the EV/CV. This may reduce the validity of the study
-Less Economical: need twice as many participants as repeated measures for the same data. This means more time is spent recruiting which is expensive
Experimental designs: Repeated Measures
Same participants take part in all conditions of an experiment. The order of conditions should be counterbalanced to avoid order effects
Repeated Measures: Positives + Explanations
-Participant variables: the person in both conditions has the same characteristics. This controls an important CV
-Fewer Participants: half the number of participants is needed than in independent groups. This means less time is spent recruiting participants
Repeated measures: Negatives + explanations
-Order effects are a problem: participants may do better or worse when doing a similar taste twice and there are also practice/fatigue effects. This reduces the validity of results
-Participants guess aims: participants may change their behaviour which may reduce the validity of results
Experimental designs: Matched pairs
Two groups of participants are used but they’re also related to each other by being paired on participant variables that matter for the experiment
Matched pairs: Positives + Explanations
-Participant variables: participants matched on a variable that’s relevant to the experiment. This controls participant variables and enhances the validity of the results
-No order effects: participants are only tested once so no practice or fatigue effects which also enhances the validity of results
Matched Pairs: Negatives + Explanations
-Matching isn’t perfect: Matching is time consuming and can’t control all relevant variables meaning not all participant variables can be addressed
-More participants: Need twice as many participants as repeated measures for the same data. This means more time is spent recruiting which is expensive
Types of experiment: Lab Experiment
A controlled environment where extraneous and confounding variables can be regulated. Participants go to the researcher. The independent variable is manipulated by the researcher and effect on the dependent variable is recorded.
Lab experiment: Positives + Explanations
-EVs+CVs can be controlled: this means that the effect of the EVs and CVs on the DV can be minimised. Cause-and-effect between the IV and DV can be demonstrated (high internal validity).
-Can be more easily replicated: greater control means less chance that new EVs are introduced. This means that findings can be confirmed, supporting their validity
Lab Experiment: Negatives + Explanations
-May lack generalisability: the controlled lab environment may be artificial and participants are aware they’re being studied. Behaviour may not be natural and can’t be generalised to every day life, which means there is no external validity.
-Demand characteristics: cues in the experimental situation that invite a particular response from participants. The findings may be explained by these keys, rather than the effect of the IV (lower internal validity).