# R.M.

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1. 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
2. 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 1-shot case studies
3. 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)
4. Contingency Table-
Tabular presentation of all combinations of categories of two variables, which allows the relationships between the two to be examined
5. Experimental Research-
Find out how things are in relation to other things and how they got that way
6. 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
7. Relational Research-
Find out how things are in relation to other things
8. 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 variables-looks 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
9. Scatter Plots-
• One way of doing relational research: look at linear correlation between predictor and outcome variable.
• Typical statistic used in Pearson
10. 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
11. Two transformations:
• 1. Percent (per hundred)
• 2. Z scores
12. Z-scores
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
13. The Standard Normal Curve has a mean of ____ and a standard Deviation of___
• 0.0
• 1.0
14. Strongest Correlation:
Both X and Y of each pair exactly same absolute distance from mean in Z score units
15. Strongest Positive Correlation:
Zx and Zy have same sign and same absolute distance from mean in Zs
16. Main idea-Pearson Product moment correlation:
Strong r if each member of pair-same relative position on its respective measure
17. Scaling-
assigning numbers to the magnitude of psychological events
18. Fechner's Law:
S = K log R
19. Weber's Law
• Sensitivity of sensory system depends on absolute strength of a stimulus.
• Difference threshold = constant x intensity of the stimulus
20. Steven's Power Law
S = k RN

Equal physical ratios are psychologically equal
21. Scaling: Psychometrics-
Assign numbers to experiences caused by stimuli that vary along a single psychological dimension
22. Regression is
symbolized by R rather than r
23. Correlations have suspect internal validity because of:
• The third variable problem
• truncated range
• Unknown direction of causation
24. The _______ ______ procedure enhances the internal validity
cross-lagged panel
25. Experiments are internally valid because:
the causal variables and the direction of causation are unknown

### Card Set Information

 Author: faulkebr ID: 106350 Filename: R.M. Updated: 2011-10-04 14:29:43 Tags: Chapter Folders: Description: Relational Research Show Answers:

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