# Coefficient of determination

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## Coefficient of determination

A measure of the goodness of fit of the relationship between the dependent and independent variables in a regression analysis; for instance, the percentage of variation in the return of an asset explained by the market portfolio return. Also known as R-square.

## R Square

In statistics, the percentage of a portfolio's performance explainable by the performance of a benchmark index. The R square is measured on a scale of 0 to 100, with a measurement of 100 indicating that the portfolio's performance is entirely determined by the benchmark index, perhaps by containing securities only from that index. A low R square indicates that there is no significant relationship between the portfolio and the index. An R Square is also called the coefficient of determination. See also: Beta.
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Whereas, R-square =.715, adjusted R-square =.518, and F = 62.3 is significant at p=0.000 with df =1.
The model summary showed R value, R-square value, F value and P-value.
The same correlation value R becomes 0.562 (p<0.05) and R-square value increases to 0.316 when the AC is added to control variables as an IV to predict AC.
Table 2 presents the results of alphas, betas and adjusted R-square by computing CAPM regression based on 10-day MAPs.
is 59.7%, R-square is 35.6%, adjusted R-square is 34.6% and estimation of the standard error is 1.044.
Finally, to understand the economic causes of the time variation of market integration, I examine the relation between the integration R-square and business-cycle related macroeconomic variables, including the unemployment rate, real estate loan growth and the default spread (Fama and French, 1989; Bernanke, Gertler, and Gilchrist 1996).
newspapers, state television (PTV), private news channels, radio Pakistan, weekly/monthly news magazines, online/internet news), bring change in R-square value.
In a given model value of R-square is quite high that cause the estimated reuts doubtful but such higher value is due to inclusion of large number of lags and having maximum significant value of lags.
where a2 = 4.378, b2 = -0.32, c2 = 95.62, d2 = -0.0007474, 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).
Regardless, when standard errors are clustered, the "text-book" adjusted R-square statistic is biased upward since the data contain far fewer independent degrees of freedom than the number of observations.

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