From df3d8d6025b906d9bc54c93fb1bc343229affffa Mon Sep 17 00:00:00 2001 From: zleyyij Date: Tue, 2 Jan 2024 14:45:20 -0700 Subject: [PATCH] vault backup: 2024-01-02 14:45:20 --- education/statistics/Correlation and Regression.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/education/statistics/Correlation and Regression.md b/education/statistics/Correlation and Regression.md index a0a493f..f5aef14 100644 --- a/education/statistics/Correlation and Regression.md +++ b/education/statistics/Correlation and Regression.md @@ -106,6 +106,10 @@ $$ y = mx + b $$ Where $y$ is the predicted value, $m$ is the slope, $x$ is the given value and the $b$ is the intercept. $$ slope = \frac{r * \sigma_y}{\sigma_x} $$ +#### Residual plots +A plot of the differences from the line. Makes it easier to see if the data is football shaped. +If a residual plot has a strong pattern, it may not be suitable for making predictions. + ### The Regression Effect - In a test-retest situation, people with low scores tend to improve, and people with high scores tend to do worse. This means that individuals score closer to the average as they retest. - The regression *fallacy* is contributing this to something other than chance error.