For instance, the R-squared values
for Model 3 and for the testing data set become 0.322, 0.023, 0.581, 0.039, 0.367, and 0.1990 for Buildings 1 to 6, respectively.
Table 3 shows the R-squared values
derived from the retrieval results using the three methods.
From the multivariate models, R-squared values
were generated to characterize the independent-variable correlations (relationships) for preirradiation controls (RC0) and the 6.5 Gy radiation dose cohort (RC3).
Fourth, there were numerous low r-squared values
which explained very little variation in the dependent variables.
Notice that the R-squared value
for UVA radiation is 0.94, and for UVB radiation it is 1 which is a good fit of the line to the experimental data.
The R-squared values
for du and We relationships were less than 0.64.
The r-squared value
for mathematics reasoning is relatively low, while the r-squared value
for Algebra I achievement is moderate, which is not unexpected due to the nature of the model.
Any candidate model which does not result in a fit parameter (adjusted R-squared value
) of 0.64 or greater was eliminated from further consideration, reducing the number of candidate models from 82 to 60.
583.606 980.143 1212.763 Maximum 4777 8625 7802.500 Minimum 0 0 -9824.800 Table 2 Estimated coefficients for the total period 1994-2003 (805 observations) Intercept 1/BVE Pos_NI/BVE Neg_NI/BVE Coefficients 4.157 * -7.500 17.669 * 2.843 * t student 5.345 -0.245 4.655 2.726 p-value 0.000 0.806 0.000 0.007 RD/BVE ADVERT/BVE SALES_gr/BVE Gr_miss Coefficients 2.055 1.205 1.576 * -1.623 t student 0.642 0.988 2.174 -0.393 p-value 0.521 0.323 0.030 0.695 R-Squared value
= 0.0037 *: denotes significance at the 5% level.
The regression models have been fitted by the best R-squared value
If, for example, a bond fund were judged against the S&P 500, the R-squared value
would be very low.
on perceived usefulness, with adjusted R-squared value
at .63 and