if m even
if m odd
if m even
if m odd
criterion compares a quadratic function of
the sums of ranks R[ of the samples with
chi-square distribution critical values,
where the degrees of freedom are the
number of samples minus one:
C-l.###Kruskall-Wallis' test on the
homogeneity of variance components for
several variances of independent samples.
This test must be used instead of classical
Bartlett's
test, when population distributions aren't
normal, although samples must be
independent. It is a generalisation of
Siegel-Tukey's rank test for two variances
under the same hypotheses.
Therefore the ranks are assigned from the
smallest absolute residual to the largest
one, after having put all samples together
and sorting their residuals, so that the
dispersion of each appears immediately.
The test criterion compares a quadratic
function of the sums of ranks R t of the
samples with chi-square distribution
critical values, where the degrees of
freedom are the number of samples minus
one:
H 0 :
P(X 2 u=/n-i(a / 2) < H < x 2 u=m-i(1 - a / 2)) = 1 - a
H 0 :
P(X 2 u= m -i(a / 2) < H < x 2 v=m-1 (1 - a / 2)) = 1 - a
where:
D. Kruskall-Wallis' test or Friedman's test on
the variance analysis of several means of
independent or correlated samples,
respectively.
### These tests must be used instead of
classical Fisher's test, when population
distributions aren't normal or there are
inequalities of dispersion of the samples,
respectively, in case of independent
samples or correlated ones. The first test
generalises Mann-Withney's rank test for
two means under the same hypotheses,
whilst the second one generalises
Thompson's sign test.
The test procedure is the same explained
for the homogeneity of variance
components; the ranks are assigned to the
arguments of the elements, obviously.
where:
12
R?
N(N+1) /=1 n,
3(/V+1)
N= In,
/'=1
C-2. Friedman's test on the homogeneity of
variance components for several variances
of correlated samples.###
This test is less powerful than the above
mentioned Kruskall-Wallis' test, but it
permits to analyse correlated samples. This
is a generalisation of Thompson's sign test
for two variances under the same
hypotheses.
Therefore the ranks are assigned to the
absolute residuals, element by element
across the samples in increasing order,
after having paired all samples. The test
Aknoledgment
The authors thank, Mr. Pasquale Pellicano
(civil engineer student) and Mr Consolato
Dattola (UTE Reggio Calabria), for their
support during the measurements.
Bibliography
AA.VV.: Guide to GPS Positioning. Canadian
GPS Associates, 1986.
T. Bellone, L. Mussio: Trattamento delle
Osservazioni. CLUP, Milano, 1996.
G. Inghilleri: Topografia generale. UTET,
Torino, 1974.
F. Sansò: Il trattamento statistico dei dati.
CLUP, Milano, 1990.