Table 6.

Analysis of variance with the number of fast muscle fibres (FN) as a dependent variable using the method of sequential sums of squares for tests

Sourced.f.Seq. SSSeq. MSFP
Model A
Treatment 8.936×104 8.936×104 25.93 0.038
Age 6.333×106 6.333×106 4539.0 0.0005
Treatment—age 3.420×104 3.420×104 8.31 0.005
Cage (treatment) 7100 3550 0.84 0.425
Error 124 5.10×105 4115
Total 129 6.974×106
Model B
Treatment 2.574×1011 2.574×1011 67.67 0.016
TCA 6.601×1012 6.601×1012 1998.6 0.0005
TCA3×treatment 9.888×1010 9.888×1010 29.94 0.0005
Cage (treatment) 7.591×109 3.796×109 1.15 0.32
Error 120 3.963×1011
Total 129 9.086×1012
Sourced.f.Seq. SSSeq. MSFP
Model A
Treatment 8.936×104 8.936×104 25.93 0.038
Age 6.333×106 6.333×106 4539.0 0.0005
Treatment—age 3.420×104 3.420×104 8.31 0.005
Cage (treatment) 7100 3550 0.84 0.425
Error 124 5.10×105 4115
Total 129 6.974×106
Model B
Treatment 2.574×1011 2.574×1011 67.67 0.016
TCA 6.601×1012 6.601×1012 1998.6 0.0005
TCA3×treatment 9.888×1010 9.888×1010 29.94 0.0005
Cage (treatment) 7.591×109 3.796×109 1.15 0.32
Error 120 3.963×1011
Total 129 9.086×1012

d.f., degrees of freedom; seq. SS, sequential sums of squares; seq. MS,sequential mean squares; F, variance ratio; P, probability.√FN was fitted as the dependent variable to normalise the residuals.

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