Sampling Distribution of Pearson's r (3 of 3)
Next section: Difference between correlations
The number of standard deviations from the mean can be calculated with the
formula:
where: z is the number of standard deviations above the z' associated
with the population correlation, z' is the value of Fisher's z' for the
sample correlation (z' =.97 in this case), μ
is the value of z' for the population correlation (.55 in this case) and
is the mean of the sampling distribution of z'.

is
the standard error of Fisher's z'; it was
previously
calculated
to be .25 for N = 19.
Plugging the numbers into the formula: z = (.97 - .55)/.25 = 1.68.
Therefore, a correlation of .75 is associated with a value 1.68
standard deviations above the mean. As shown
previously, a z table can be used to
determine the probability of a value more than 1.68 standard
deviations above the mean. The probability is .95. Therefore there is
a .05 probability of obtaining a Pearson's r of .75 or greater when
the "true" correlation is only .50.
Next section: Difference between correlations