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Are changes in X causes of changes in Y?
 1. Show that "delta" in Y did not occur until after "delta" in X
 2. Show that X and Y are related. The cause and effect must be correlated with each other
 3. Show that other explanations for the relationship between X and Y can be ruled out.
 4. Plausible causal link between X and Y

Descriptive Research: Find out how things are
Example facial expressions eyebrow flash
 1. Important research method
 2. Sometimes first step in research program
 3. Often called case studies or 1shot case studies

Relational Research: Find out how things are in RELATION to other things
Example Word usage and length of word; Social context and eyebrow flash
Can show that X and Y are related (covariation rule)

Contingency Table
Tabular presentation of all combinations of categories of two variables, which allows the relationships between the two to be examined

Experimental Research
Find out how things are in relation to other things and how they got that way

Experimental research:
Independent variable and dependent variable
 1. Show that delta in Y did not occur until after delta in X
 2. Show that X and Y are related
 3. Show that other explanations for the relationship between X and Y can be ruled out

Relational Research
Find out how things are in relation to other things

Relational research: find out how things are in relation to other things:
 Measure the degree of relationship between 2 or more naturally occuring characteristics, behaviors,or variables.
 Researcher doesnt change the value of the variableslooks at natural occurances
 Thus no I.V.no manipulation
 Predictor Variable(first possible cause) & outcome variable (second: possible effect)
 Ex. Gender and helping behavior, Growth in hippocampus & depression, height and shoe size

Scatter Plots
 One way of doing relational research: look at linear correlation between predictor and outcome variable.
 Typical statistic used in Pearson

Pearson Correlation Coefficient: Sometimes transform data by performing some standard mathematical operation on each score. Transform data for a number of reasons:
 1. to obtain more convenient numbers
 2. to meet the assumptions of certain stats
 3. toobtain pretty graphs
 4. to meet the assumptions of some theory
 5. to minimize the influence of extreme scores
 6. to allow for comparison across different data sets such as diff. psychological tests or college examinations

Two transformations:
 1. Percent (per hundred)
 2. Z scores

Zscores
How far the score is from the mean in standard deviations units
 1. measure of relative position
 2. Can compare pple on different measures even if scales are different
 3. Convert set of scores to z scores: mean = 0.0 and standard deviation = 1.0

The Standard Normal Curve has a mean of ____ and a standard Deviation of___

Strongest Correlation:
Both X and Y of each pair exactly same absolute distance from mean in Z score units

Strongest Positive Correlation:
Zx and Zy have same sign and same absolute distance from mean in Zs

Main ideaPearson Product moment correlation:
Strong r if each member of pairsame relative position on its respective measure

Scaling
assigning numbers to the magnitude of psychological events

Fechner's Law:
S = K log R

Weber's Law
 Sensitivity of sensory system depends on absolute strength of a stimulus.
 Difference threshold = constant x intensity of the stimulus

Steven's Power Law
S = k R^{N
}Equal physical ratios are psychologically equal

Scaling: Psychometrics
Assign numbers to experiences caused by stimuli that vary along a single psychological dimension

Regression is
symbolized by R rather than r

Correlations have suspect internal validity because of:
 The third variable problem
 truncated range
 Unknown direction of causation

The _______ ______ procedure enhances the internal validity
crosslagged panel

Experiments are internally valid because:
the causal variables and the direction of causation are unknown

