STANDARD SCORES, NORMAL CURVE, & NORMAL DISTRIBUTION Flashcards
Types of Standard Scores
z-scores t-scores Deviation of 12 scores Normal curve equivalents Stanines Percentile ranks
This standard score describes a score in terms of how much it is above or below the average. It makes it easier to determine underlying raw score’s location, its relative and simple frequency, and its percentile.
z-scores
Reflects systematic evaluation of a score relative to the sample or population in which the score occurs.
Relative standing
raw score to z-scores
Population: z= (x-mean)/std. dev
Sample: z= (x-mean)/std. dev
z-scores to raw score
Population: x= (z)(std. dev) + mean
Sample: x= (z)(std. dev) + mean
proportion of time that a score occurs
relative frequency
Also called fifty plus or minus ten scale. A scale with a mean of 50 and standard deviation of 10. Developed by W.A. McCall and named after E.L. Thorndike.
t-scores
Formula of t-scores
T= 10z+50
Well known from World War 2. It has a mean of 5 and a standard deviation of 2. It is divided into 9 units.
Stanine
This presents frequency according to the raw score.
Normal Distribution
This presents frequency according to the z-score.
Normal Curve
It is the far left and right portions of a normal curve.
tails
Kurtosis Property
Mesokurtic
Platykurtic
Leptokurtic
A Kurtosis Property in which the tail is neither too thin nor too thick. The peak is not too many or too few.
Mesokurtic
A Kurtosis Property in which the peak is too flat.
Platykurtic
