vault backup: 2024-01-02 14:45:20
This commit is contained in:
parent
c9760395c2
commit
df3d8d6025
@ -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.
|
Where $y$ is the predicted value, $m$ is the slope, $x$ is the given value and the $b$ is the intercept.
|
||||||
$$ slope = \frac{r * \sigma_y}{\sigma_x} $$
|
$$ slope = \frac{r * \sigma_y}{\sigma_x} $$
|
||||||
|
|
||||||
|
#### 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
|
### 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.
|
- 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.
|
- The regression *fallacy* is contributing this to something other than chance error.
|
||||||
|
Loading…
Reference in New Issue
Block a user