=.715, value of adjusted R-square
=.710, and F = 145.7 is significant at p = 0.000 with df =1.
The Model summary showed that R-Square
value for Employee Retention was.043 presenting 43% variations in the model by the dependent variable which supports the research study.
The same correlation value R becomes 0.563(p<0.05) and R-square
value increases to 31.7% when the POS is added to control variables as an IV to predict AC.
Risk-adjusted returns also show comparable results as of raw returns with high R-Square
values of 44% on average across quintiles implying the strength of the model and the accuracy of results.
A moderate positive relationship between age of patients and number of traction was observed in our data with R-square
of 0.442, on contrary Marchi CH et al.11 reported no correlation with R-square
The outcome of model summary is based model having 1, regression is denoted by R i-e 59.7%, R-square
is 35.6% and adjusted R-square
For example, I uncover 3-4 cyclical movements of the integration R-square
in the EREIT market in the 1972-2001 period (before the latest 2001-2010 cycle), while the national housing market integration is relatively stable in the 1992-2001 period.
The predictive model in table 5 indicates that the predictors (leadership styles of owner-managers: transactional, transformational, autocratic, charismatic and visionary) and age account for 6.52% change in employees' output (R-square
age, gender, income and education,) have been entered and subsequent R-square
value is recorded 2.5 % for this model.
However, goodness of fit of the model is arbitrated through R-square
value which is 98 percent presenting that variation in productivity due to average rain fall, credit disperse, average temperature and fertilizer use is 98 percent while ramining 2 percent is due to other factors that are included in error term.
where a1 = 5.064, b1 = -0.02817, c1 = 94.91, d1 = -0.0004108, and "x" is the MgO concentration ([micro] x [ml.sup.-1]) (SSE: 0.8483, R-square
: 0.9969, adjusted R-square
: 0.9923, and RMSE: 0.6513).
El segundo programa usado fue el Software matematico Matlab en su version 18.104.22.1685 (R2011a); de el se utilizo la herramienta Curve Fitting Toolbox 3.1, Copyright 20012011 The MathWorks Inc, con la cual se hallo la ecuacion (1) que se presenta al final de la seccion III y se estimaron los parametros estadisticos de la regresion, como el SSE, R-square
, el Adjusted R-square
y el RMSE.