Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
14 Cards in this Set
- Front
- Back
|
Quasi-independent experimental variables |
Characteristics that can't be randomly assigned
Gender, age, ethnicity |
|
|
True experimental variables |
you can control these you can randomly assign people to groups
Drug treatment A or B |
|
|
True experimental designs: |
Also known as randomised designs researchers can randomly assign participants to different experimental condition
|
|
|
Quasi experimental design |
Similar to experimental designs but research is unable to randomly assign participants to groups |
|
|
Confounding variables |
if the groups to be compared differ in ways other than which the researcher has manipulated
|
|
|
Independent variable |
Condition or event that you are controlling |
|
|
Dependent variable |
Variable that you are measuring |
|
|
Randomisation |
Ensures that each participant is equally likely to be assigned to a given condition |
|
|
3 reasons for randomising |
-Prevents experimenters (un)intentialy biasing their results -Distributes the occurrence of potential moderating/confounding variables equally among experimental conditions -Enables the use of powerful statistical tests that can help determine causal relationships between variables |
|
|
Two ways of comparing groups/conditions |
Independent groups (between-subjects) Repeated measures (within-subjects)
|
|
|
Problem with independent group designs |
Confounding factors between the two groups - can fix this by ensuring the groups are matched as closely as possible on potential confounding variables
|
|
|
Repeated measures design: potential problems |
Order effects Once participants have been exposed to one level of the IV theres no way to return them to their original state: Practice effects, fatigue effects |
|
|
Counterbalancing: how to get around order effects |
Randomly assign participants into group A or group B, and have them take part in the experiment in different orders
Order effects not eliminated but should be common to both conditions |
|
|
Internal validity |
How correct is it to claim that treatment X causes outcome O?
Has the study managed to prevent confounding variables |
