is calculated
as SS/n-1, rather than as SS/n, and that therefore it
is the unbiased estimator of 
2,
the population
variance.
Define what is meant by a biased and unbiased estimator.
Recognize that
is calculated
as SS/n-1, rather than as SS/n, and that therefore it
is the unbiased estimator of 2,
the population
variance.
Recognize that s , that is, the square root of ,
although not itself an unbiased estimator of sigma, is still the best estimator
of sigma because it is based on the unbiased variance.
Define degrees of freedom and state the number of df associated with
.
Calculate
or s either
from a set of raw scores or given a sample sum of squares (SS) and n.
Given either (a)
X,
X2,
and n, or (b) SS and n, or (c)
or s, calculate
the estimated standard error of the mean,
(
), as opposed to the actual
standard error of the mean
().
Explain why the t test must be used rather than the normal curve test to
test hypotheses about a population mean when
2
is not known.
Describe characteristics of the t distribution and the effect of df on the shape of the distribution.
Given n and alpha, use the t table to find the critical value of t (tc) for a one tailed or a two tailed test.
Given relevant information, decide whether a normal curve test or a t test is required.
Given a research hypothesis, a level of alpha, and sample
,
or s, and n: