1, 2, 3, 4, 7 and 9. The data fell on nearly a straight
Table 5. Analysis of variance.
line, indicating that they are random and normally
distributed. Bartlett's test for homogeneity of the
error variance showed that the variances were not
range test indicated that sets 3 and 9 should not be
included, and Table 5 contains the results of a
series of ANOVA tests to determine which of the
data could be combined.
Between each ANOVA test, a procedure fol-
lowing Grubbs (1969) was used to determine if the
extreme values could be considered outlying ob-
servations. This analysis also showed that sets 3
and 9 can be dropped from further analysis on the
For all data sets
basis of statistical arguments. The average rear tire
motion resistance coefficient Rr/Vr of the remain-
interval of 0.0138 to 0.0199. These values are shown
graphically on Figure 6. It should be noted that if
both sets 3 and 9 are included, the average Rr/Vr
is 0.0167 with a confidence interval of 0.0127 to
Since F0.95 (5,32) = 2.5, there is a difference between data sets.
0.0207, which really isn't much different from the
values obtained from the four data sets, although
For data sets 1,2,3,4 and 7
it is serendipitous that the effects of these two tests
(3 and 9) average each other out.
From the above analysis, it appears that a trail-
ing tire in dry snow that is less than 0.22 m deep
and that has a density less than about 0.250 Mg/m3
will have a resistance coefficient of about 0.017,
although values as low as 0.0 and as high as 0.64
Since F0.95(4,29) = 2.7, there is a difference between data sets.
were measured. No data were obtained for snow
densities greater than 0.250 Mg/m3. It should also
be noted that the rear wheels of the CIV carry less
For data sets 1,2,4 and 7
weight than the front wheels, and the effect of a
trailing tire carrying a higher weight is not known.
Tests 0125f0125i (data set 5) were done in
relatively deep snow compared to the other tests.
These deep snow tests resulted in limited data for
Since F0.95(3,22) = 3.05, there is no difference between data sets.
two different trailing tire configurations. Data were
obtained similar to those described above (all four
wheels of the CIV rolling freely in undisturbed
agree with the other data (Table 4). There was no
snow) and with the front wheels driving while the
apparent reason for this on the basis of test condi-
rear wheels were rolling free. This second condi-
tions or procedure, although data set 9 may have
tion, freely rolling wheel trailing a driven tire, is
been collected in hard "crusty" snow. To legiti-
significantly different from that described earlier.
mately combine these data sets, the data need to be
To tow the CIV through this deep (36 cm) snow,
random and normally distributed and the vari-
a packed path was first made for the lead vehicle.
ances need to be homogeneous. Once this is shown,
Additionally, the snow was deep enough such
an analysis of variance (ANOVA) test or multiple
that the undercarriage of the lead vehicle dis-
range test can be used to determine if the data sets
turbed the snow in which the right side wheels of
can be combined.
the CIV traveled. Thus, in Table 3, for tests 0125f
and 0125g, data are only presented for the left side