I have made two linear regressions to estimate y and I get this results: One:
Residual standard error: 1.021 on 276 degrees of freedom Multiple R-squared: 0.2347, Adjusted R-squared: 0.2059 F-statistic: 8.362 on 10 and 276 DF, p-value: 6.878e-12
Residual standard error: 1.025 on 273 degrees of freedom Multiple R-squared: 0.2312, Adjusted R-squared: 0.1945 F-statistic: 6.314 on 13 and 273 DF, p-value: 2.085e-10
I know from $R^2$ that these models are not good, but which one is better from the other one? Can someone can explain the other factors beside R-squared? Maybe use ANOVA to compare?