It can be observed that ASHRAE Handbook and regression equation
results are in octave bands, whereas measured and FEM results are in 1/3-octave bands.
m) of the variables and for the free term b in the regression equation
indicates whether or not the relevant variables or the free term are significant.
To the best of author knowledge, until now, no study has been published to determine the reliability of the two mentioned methods, so the aim of the present study was to compare the sum mesiodistal widths of the maxillary and mandibular incisors using Tonn's and Abhi's methods with the actual mesiodistal widths and, at the same time, to formulate regression equations
to predict the sum mesiodistal widths of the maxillary and mandibular incisors and compare them with the actual and previous methods.
The direct and indirect effects of selected morphological traits on body weight on multiple regression equations
were then determined using path correlation analysis.
In order to improve the accuracy of prediction of observed BW from linear body measurement, multiple linear regression equations
along with dental cast is the only solution in such cases if these have a reasonable degree of validity.
We also derived a multiple linear regression equation
to predict gestational age from CHL and HC in a whole cohort.
The best regression equation
for a calibration curve should have the following characteristics (without distinguishing the subscripts O and UW): (i) intercept b small approaching to zero; (ii) slope m large; and (iii) both [u.sub.b] and [u.sub.m] small.
The regression equation
derived from the left foot index of males is given in Table 2.
Our results demonstrated that when PV/TV ratio was used as an index, a linear regression equation
for individual age was established: Y=69.137-621.200 (PV/TV), R=0.544; the inferred function of male age: Y=64.333-468.811 (PV/TV), R=0.435; the inferred function of female age: Y=76.445-843.186 (PV/ TV), R=0.691.
The slope of the regression line represented the TTTD of AEE, with the y-intercept of this regression equation
being considered the ELF of AEE (g/kg of DMI).
The empirical model developed using regression equation
includes main factors and first order interaction of all factors.