title: R - calculating 95% confidence interval for R-squared and residual standard error by boot strap linear model
body: <p>I'm new to R and am trying to calculate the 95% confidence intervals for the R-squared values and residual standard error for linear models have formed by using the bootstrap method to resample the response variable, and then create 999 linear models by regressing these 999 bootstrapped response variables on the original explanatory variable.</p>
  
  <p>First of all, I am not sure if I should be calculating the 95% CI for R-squared and residual standard error for the ORIGINAL linear model (without the bootstrap data), because that doesn't make sense -  the R-squared value is 100% exact for that linear model, and it doesn't make sense to calculate a CI for it.</p>
  
  <p><strong>Is that correct?</strong></p>
  
  <p>Importantly I'm not sure how to calculate the CI for the R-squared values and residual standard error values for the 999 linear models I've created from bootstrapping.</p>