Chapter 5: Z-scores Flashcards
Z-scores
The number of standard deviations a given score is from the mean
Population z score formula
population z= x-μ/ σ
Population x value formula
population x= μ + zσ
Sample z-score formula
sample z= x-M/s
Sample x value formula
sample x= M + zS
2 properties z-scores reveal
- the sign reveals whether the x value is located above or below the mean
- the numerical value of the z-score corresponds to the number of standard deviations between X and the mean of the distribution
the mean of the z-score distribution is
0
the standard deviation of the z-score distribution is
1
most z-score values (95%) are between
+2 and -2
advantage of standardizing distributions
2 or more distributions can be compared in the same metric
t or f: transforming a dataset into a z-score distribution changes its shape
false; its shape stays the same
z-scores as a descriptive statistic
describe exactly where each individual is located
z-scores as an inferential statistic
determine whether each specific sample is representative of the population
standardizing distributions based on z-scores
- select the new mean and standard deviation that you would like for the distribution
- use the z-scores to identify each individual’s position in the original distribution to compute the individual’s position in the new distribution
raw score
the original unchanged score