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Foss Donald
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University of Houston

Psychology

PSYC 2301

Foss Donald

Spring

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Test 3 Methods Review
New Topics to Cover
Correlation Facts
o Difference Between Negative and Positive Correlation
Negative: linear relationship increases the values of one variable are
accompanied by a decrease in the values of the other variable (Graph B pg
73)
Positive: Increase the values of one variable are accompanied by increases
in the values of the second variable (Graph A pg. 73)
Scatter Plots
o Graphic representation of each individual’s scores on two variables. The score on
the first variable is found on the horizontal axis and scores on the second variable
are found on the vertical axis
o Single point in the diagram
o Perfect positive relationship is +1.00
o Perfect negative is -1.00
o Pearson’s r correlation Coefficient
To calculate a correlation coefficient, we need to obtain pairs of
observations from each subject
Individuals have two scores, one on each of the variables
The Pearsons r provides two types of information, strength of relationship
and direction of relationship
Correlation is not the same as causation
CORRELATION COEFFICENT IS USED TO REPRESENT THE
DEGREE OF RELATIONSHIP BETWEEN TWO VARAIBLES
Effect on correlation of “restricted range”
o If the range of possible values is restricted, the magnitude of the correlation
coefficient is reduced
o With restricted range comes restricted variability in the scores and thus less
variability that can be explained o Restriction of range: occurs when the individuals in your sample are very similar
on the variable you are studying
Ex: If you are studying age as a variable, testing only 6 and 7 year olds
will reduce your chances of finding age effects
Effect Size
o Refers to the strength of association between variables
The Pearsons r correlation coefficient is one indicator of effect size; it
indicates the strength of the linear association between two variables
Reliability and Validity:
o How tests are assessed
o Reliability: the correlation of the test with itself
The higher the correlation the higher the reliability
Low correlation is unreliably
o Validity
The correlation of a test with external criterion
Higher the correlation, the higher the validity
Lower correlation is lower validity
o A test has to be reliable to be valid
o Reliability is necessary for validity
Inferential Stats
o Population Vs. Sample
Inferential statistics are used to determine whether the results match what
would happen if we were to conduct the experiment again and again with
multiple samples
Population is what we want to know about so we select a sample from the
population
Parameter: Population; Sample: Statistic
We care more about the parameter than the statistic
So we want to generalize from the sample to the population- to
make an inference o The Decision Logic
The clai

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