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Table 4 Summary of Hierarchical Regression Analysis for Variables Predicting Reading Achievement

PACER

.56

.09

.40***

BMI

−.83

.31

−.15**

Push-ups

.12

.14

.05

Curl-ups

.13

.10

.08

Sit and reach

.02

.47

.002

Age

−1.9

Sex

1.7

School

6.8

β

−.07 .04 .16

# Variable

B

*p < .05, **p < .01, ***p < .001.

Step 2

SE B

Step 1 1.7 2.6 2.6

The Step 1 regression analysis for mathematics achievement was not signifi- c a n t , a d j u s t e d R 2 < . 0 1 , F ( 3 , 2 5 5 ) = 1 . 8 , p = . 1 5 , i n d i c a t i n g t h a t a g e , s e x , a n d s c h o o were unrelated to performance in mathematics achievement. The Step 2 regression l a n a l y s i s w a s s i g n i fi c a n t , R 2 = . 2 8 , F ( 5 , 2 5 0 ) = 1 9 . 9 , p < . 0 0 1 . T h e r e w e r e s i g n i fi c a effects for BMI, pr = .15, t(250) = 2.3, p = .02, β = .13, and for PACER, pr = .41, t (250) = 7.1, p < .001, β = .42, indicating that lower BMI and higher aerobic fitness were positively related to mathematics achievement (see Table 5). n t

Variable

B

SE B

β

Age Sex School

−1.9 3.5 5.0

Step 1 1.8 2.6 2.7

−.07 .08 .12

Step 2

PACER

.61

.09

.42***

BMI

−.73

.32

−.13*

Push-ups

.09

.14

.04

Curl-ups

.10

.10

.06

Sit and Reach

.83

.48

.10

Table 5 Summary of Hierarchical Regression Analysis for Variables Predicting Mathematics Achievement

*p < .05, **p < .01, ***p < .001.

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