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Independent vs. dependent variable
(IV) - what the researcher manipulates
(DV) - what the researcher is measuring
Null vs. research hypothesis
null: proposes no relationship & difference between the two variables. We predict no relationship between x and y. (example: the level of noise has no effect on one's test scores in mathematics.)
research: proposes a relationship between variables (the louder the noise, the lower the test score)
x does not cause y but x and y seem to always be together
-we cant tell if one thing causes another
Revealing of and justifying aim and purpose of the research collected. This must be done at the end of all studies.
Repeated measures design
uses the SAME SUBJECTS in each condition of the experiment (ex: driving test w/ alcohol and later w/out)
-subject variables kept constant/same
-better statistical tests
-order effects (learning, fatigue, boredom)
-demand characteristics (refer to Psych 1 Aug.29-Sept.2)
-different tests may be needed
Independent samples design
uses DIFFERENT SUBJECTS in each condition of the experiment (ex: 1 driving test w/out alcohol then diff. group for a test w/ alcohol)
-order effects don't have an influence
-the same test can be used
-subject variables differ
-worse statistical tests
-more subjects required
one in which every member of the target population has an equal chance of being selected. (classroom: sorting 1 person out of hat)
Sample of opportunity
already is there (ex: a class in school at the time of the study).
sample of people that is available at the time
interviewer arbitrarily selects people for survey
(ex: collecting people on the street)
select people based on the purpose of the study/a focus a person has (ex: do you take cocaine?)
Snowball (network) sample
when you use one member of sample to help you find other members of sample (trust gaining)
(ex: talk to 1 drug dealer & gain his/her trust & ask him/her to introduce you to more drug dealers)
participant acts differently because he/she knows they are in an experiment or what experiment he/she is in
(the participants want to help the researcher so he/she answers accordingly)
Laboratory environments and operationalized variables may lack ecological variability (DOUBLE CHECK THIS)
-Example: One class takes a test and then a person who has just taken the test tells another class what is on the test, thus affecting the test results
Maturation (order effects)
the order you choose may affect experiment (play a game 3 times, you get better at it by the 3rd time)
variables over which you have no control and which negatively impact your experiment
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