Table 5.

Hierarchical multiple regression

Block	Predicting Variable	t	β	F change	R2 change	F	R2
1	Weight	14.127	.701***			310.351***	0.878
	Sex	−4.272	−.231***
2	Knee extension strenght	2.012	.124*	4.048*	0.005	215.756***	0.882

Parameters in regression model *p < 0.05, **p < 0.01, ***P < 0.001

Note: t- The t statistic is the coefficient divided by its standard error. β is the normalized coefficient, the highest its absolute value, the variable have more influence on the depended variable. The F value in regression is the result of a test where the null hypothesis is that all of the regression coefficients are equal to zero. R² - coefficient of determination is a statistical measure of how well the regression predictions approximate the real data points