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the amount of discreptency between an empirical score and a true score that we would exoect from any member in a sample
Sample Standard Deviation
the combined set of variations from the mean in a sample, geometrically represented as an area
sample variance
the number of units a particular score of an individual is "away" from an alleged true score
standard deviation
the score expected in any person who is a member of a group
sample mean
the scores of the majority of the members in a sample would differ from the mean by this much
standard deviation or deviation from the mean
mathematically the product of the mean & sample size
sample mean
attribute in an ordinal dataset where 50% of observations are below it
median
mathematically, it is estimated as the ratio between SS & N
sum of squares
nominal attribute that has the highest frequency
mode
number of standard units a certain score is above or below the true score
standardized score
number of times an empirical deviation from the mean is to the typical extent of variation in a sample
standard deviation
the degrees of freedom is always dependent on this statistical value
sample size
value that takes into account the actual score relative to the mean
z-score
if you multiply this by the df, u get to estimate the total amount of information about a variable that was observed in a sample
sample variance
an empirical attribute in either an interval or ratio level of measurement
deviation from the mean
two-dimensional geometric representation of how different an empirical score is from a theoretical score
standardized score
gravitational center of dataset
mean
number of observations that can vary when a sample of size is drawn again from population
sample size
amount of variation from the mean you should observe from a typical member in a sample
standard deviation (?)
attribute you empirically observed per one member in a sample
raw score
Note 
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