#### Unit 1

Quantitative Data

Based on Numeric Data.
Example: experiment, correlations

Quantitative Data

Based on Descriptive Data.
More subjective, more difficult to analyze.

Covert Observations

Observations when the person/animal you are observing does not know they are being observed.

Overt Observations

When the person/animal knows they are being observed.

Non-participant

Not participating but observing a situation.

Participant

Participating in a situation as a part of observing.

Case Studies

Naturalistic or an intense study of an individual or a group.
(looking at EVERYTHING/ whole person)

Triangulation

Observing , MRI (brain scans), memorization tests, interviewed, and THEN concluding.

Levels of Data

Nominal, Ordinal, Interval, Ratio.

Correlational Studies

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.

Bidirectional Ambiguity

It is not apparent if x causes y, y causes x, or if there is no cause and effect relationship at all.

Haphazard Sample

By chance, a person stands on a streen and asks questions to passers by.

Random Sample

Everyone has the same chance to be in the study.

Stratified Sample

A group in general population are proportionally represented.

Heuristic Value

When a theory can be applied to different situations
(Example: Schema, SLT)

Predictive Validity

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?)

Placebo Effect

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.

Contamination

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.

Independent Variable

Controlling one variable.

Alternative Hypothesis

Other than a null hypothesis. What you think is going to happen.

Dependent Variable

What you measure.

Demand Characteristics

When a subject thinks they are suppose to act in a certain way and they do.

Deceit

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.

Intervening Variables

The researcher can't do anything about it.
Example: The participant is sick.

Berevment Theory

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.

Ecological Validity

The study is so controlled that it doesn't have any aspects of how it is in real life.

Expectancy Effect

The participants do what they are expected to do.

Double Blind Control

When neither the participant nor the researcher know everything about the experiment.

Null Hypothesis

Predicting nothing is going to happen.

Confounding Variables

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.

Repeated Measures

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.

Independent Measures

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.