vault backup: 2024-01-02 14:18:59

This commit is contained in:
zleyyij 2024-01-02 14:18:59 -07:00
parent cd16ffaf94
commit e1469468d7

View File

@ -113,7 +113,7 @@ $$ \sqrt{1-r^2}(\sigma_y) $$
- On a least squared regression line, the 1 r.m.s error away will contain $2\sigma$ of the data, and it should loosely mirror a normal curve. - On a least squared regression line, the 1 r.m.s error away will contain $2\sigma$ of the data, and it should loosely mirror a normal curve.
- To approximate the R.M.S error for a scatter diagram, take a high value and a low value for a given $x$ coordinate, and divide by 4, because r.m.s error is within $2\sigma$ of either side of the line. - To approximate the R.M.S error for a scatter diagram, take a high value and a low value for a given $x$ coordinate, and divide by 4, because r.m.s error is within $2\sigma$ of either side of the line.
- 68% = $2\sigma$, 95% = $4\sigma$ - 68% = $2\sigma$, 95% = $4\sigma$
- RMS can help determine which observations are outliers. Typically if a value is more than *2 r.m.s* away from the prediction estimate, it is considered to be an outlier.
--- ---
# Terminology # Terminology
| Term | Definition | | Term | Definition |