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Chapter 5: zscores
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View Full Document zScores and Location
•
By itself, a raw score or X value provides very
little information about how that particular score
compares with other values in the distribution.
•
A score of X = 53, for example, may be a
relatively low score, or an average score, or an
extremely high score depending on the mean
and standard deviation for the distribution from
which the score was obtained.
•
If the raw score is transformed into a zscore,
however, the value of the zscore tells exactly
where the score is located relative to all the
other scores in the distribution.
Purposes of Transforming X
values into Zscores
•
Each zscore tells the exact location of the
original X value within the distribution
•
The zscores form a standardized
distribution that can be directly compared
to other distributions that also have been
transformed into zscores.
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View Full Document zScores and Location (cont.)
•
The process of changing an X value into a z
score involves creating a signed number, called
a
zscore
, such that
a. The sign of the zscore (+ or
–) identifies
whether the X value is located above the
mean (positive) or below the mean
(negative).
b. The numerical value of the zscore
corresponds to the number of standard
deviations between X and the mean of the
distribution.
zScores and Location (cont.)
•
A score that is located one standard
deviation above the mean will have a z
score of +1.00. A zscore of +1.00 always
indicates a location above the mean by
one standard deviation.
•
A score that is located two standard
deviations above the mean will have a z
score of +2.00.
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View Full Document Transforming back and forth
between X and z
•
The basic zscore definition is usually
sufficient to complete most zscore
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This note was uploaded on 09/21/2009 for the course PSY 360 taught by Professor Tamrabeckman during the Spring '09 term at University Of Southern Mississippi .
 Spring '09
 TamraBeckman

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