Based on Numeric Data.
Example: experiment, correlations
Based on Descriptive Data.
More subjective, more difficult to analyze.
Observations when the person/animal you are observing does not know they are being observed.
When the person/animal knows they are being observed.
Not participating but observing a situation.
Participating in a situation as a part of observing.
Naturalistic or an intense study of an individual or a group.
(looking at EVERYTHING/ whole person)
Observing , MRI (brain scans), memorization tests, interviewed, and THEN concluding.
Levels of Data
Nominal, Ordinal, Interval, Ratio.
Used to look for relationships between variables.
Three possible results: a positive (aka direct) correlation, a negative (aka inverse) correlation, and no correlation.
The Correlation Coefficient
Measure of correlation strength and can range from -1.00 to +1.00.
It is not apparent if x causes y, y causes x, or if there is no cause and effect relationship at all.
By chance, a person stands on a streen and asks questions to passers by.
Everyone has the same chance to be in the study.
A group in general population are proportionally represented.
When a theory can be applied to different situations
(Example: Schema, SLT)
Can the study consistently and accurately predict human behavior? (Example: in a study 2/3 of the participants conformed, but what about the 1/3, why didn't they?)
Doing something you believe makes you better
example: giving a person decaf coffee, but telling them it's normal coffee and they don't feel tired anymore.
Social Desirability Effect
Desire to be accepted.
When you "lie" so you can look better as a person to the other person when your belief is the opposite.
Doing better because someone who did it before you told you.
example: When your History Exam is before another History class's exam and you tell the other class what was on the exam.
Controlling one variable.
Other than a null hypothesis. What you think is going to happen.
What you measure.
When a subject thinks they are suppose to act in a certain way and they do.
You should never do it, unless you absolutely have to.
Example: The researcher should tell the participant as little as possible so that their knowledge does not effect the experiment.
The researcher can't do anything about it.
Example: The participant is sick.
A famous person died and people want to sacrifice themselves for the person.
Artificiality (Mundane reality)
The study is so controlled that it does not relate to how it is in real life.
The study is so controlled that it doesn't have any aspects of how it is in real life.
The participants do what they are expected to do.
Double Blind Control
When neither the participant nor the researcher know everything about the experiment.
Predicting nothing is going to happen.
The researcher should have controlled, but didn't.
Maturation (Order Effects)
Learned something so you do better.
Example: When the participant is asked to take a test once and then asked to take the same test again but they perform better the second time because they remember the test.
Categorical Variable (CV)
An Independent Variable that you cannot manipulate.
Using the same subjects for one study in each of an experiment.
Example: giving a group of subjects a test without distractions, and later giving them another test with distractions.
Using different subjects in each condition of the experiment.
Example: giving one group of subjects a driving test with no alcohol, and different group of subjects the same test after a pint of lager.