Creating
ASSESSMENTS Module 2
Session Objectives
At the end of this session you should be able to :
• • •
Interpret
SCORES NORM REFERENCING
Understand Classify
NORMS
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Norms
NORMS are a set of scores from clearly defined samples. Importance of standardizing a NORM is that it gives test scores meaning and thus makes interpretation possible.
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Score - Interpretation
Scores are commonly interpreted by
reference to norms that represent the
test performance of the standardization sample.
Understanding NORMS
•
Norms help us in
Understanding the Relative Standing / Position of the Score within a SET In comparing the performance of an individual in different tests
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Setting NORMS
•
NORMS should be ACCURATE ADEQUATE (size) & APPROPRIATE (representativeness) SAMPLING
SUPPORTED BY
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Norms
It is not so important to standardize NORMS in cases of Psychometric analysis of individual differences – the scientific study of human attributes, personality, motivation…
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Classifying NORMS
•
The 2 different forms of classification are Percentile Standard Scores
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Percentile
•Percentile scores are expressed in terms of the percentage of persons in the standardization sample who fall below a given raw score. •For example, if 28% of the persons obtain fewer than 15 problems correct on an arithmetic test, then a raw score of 15 corresponds to the 28th Percentile (P 28)
Standard Scores
•Standard scores express the individual’s distance from the mean in terms of the standard deviation of the distribution. Linearly derived standard scores are often designated simply as “standard scores” or “z scores”. •Any raw score that is exactly equal to the mean is equivalent to a z score of zero. z = (X – M)/