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  1. The standard error of the estimate is a measure of the accuracy of predictions. The regression line is the line that minimizes the sum of squared deviations of prediction (also called the sum of squares error), and the standard error of the estimate is the square root of the average squared deviation.

  2. The standard error of the estimate for a population = sqrt[(1-rho2)*SSY/N] = sqrt[(1-.52)*50/100] = .61

  3. The standard error of the estimate for a sample = sqrt[SSE/(N-2)] = sqrt[5.8/8] = .85

  4. The standard error of the estimate for a sample = sqrt[SSE/(N-2)]. SSE is the sum of the squared errors of prediction, so SSE = (-.2)2 + (.4)2 + (-.8)2 + (1.3)2 + (-.7)2 = 3.02; sqrt(3.02/3) = 1.0

Callback before_footer in local_aigrade component should be migrated to new hook callback for core\hook\output\before_footer_html_generation
  • line 7225 of /lib/moodlelib.php: call to debugging()
  • line 7292 of /lib/moodlelib.php: call to {closure}()
  • line 71 of /lib/classes/hook/output/before_footer_html_generation.php: call to get_plugins_with_function()
  • line 987 of /lib/classes/output/core_renderer.php: call to core\hook\output\before_footer_html_generation->process_legacy_callbacks()
  • line 154 of /mod/book/view.php: call to core\output\core_renderer->footer()