title: Identify the outliers with the highest squared residuals under the Linear regression model in R
body: <p>I have a data set [1000 x 80] of 1000 data points each with 80 variable values. I have to linearly regress two variables: price and area, and identify the 5 data points that have highest squared residuals. For these identified data points, I have to display 4 of the 80 variable values.</p>
  
  <p>I do not know how to use the residuals to identify the original data points. All I have at the moment is:</p>
  
  <pre><code>model_lm &lt;- lm(log(price) ~ log(area), data = ames) 
  </code></pre>
  
  <p>Can I please get some guidance on how I can approach the above problem</p>