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vault backup: 2024-01-03 14:03:11

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zleyyij 2024-01-03 14:03:11 -07:00
parent d80195ac94
commit 751681d3e0
2 changed files with 3 additions and 1 deletions
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2
.obsidian/plugins/obsidian-git/data.json vendored
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@ -2,7 +2,7 @@
"commitMessage": "vault backup: {{date}}", "commitMessage": "vault backup: {{date}}",
"autoCommitMessage": "vault backup: {{date}}", "autoCommitMessage": "vault backup: {{date}}",
"commitDateFormat": "YYYY-MM-DD HH:mm:ss", "commitDateFormat": "YYYY-MM-DD HH:mm:ss",
"autoSaveInterval": 1, "autoSaveInterval": 5,
"autoPushInterval": 0, "autoPushInterval": 0,
"autoPullInterval": 5, "autoPullInterval": 5,
"autoPullOnBoot": false, "autoPullOnBoot": false,

2
education/statistics/Correlation and Regression.md
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@ -104,6 +104,8 @@ $$ \hat{y} = \frac{x-\bar{x}}{\sigma_x} * r * \sigma_y + \bar{y} $$
Predicting a y value for a given x value can be calculated when given the regression equation. Predicting a y value for a given x value can be calculated when given the regression equation.
$$ y = mx + b $$ $$ y = mx + b $$
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.
$$ intercept = \bar{y} - $$
$$ slope = \frac{r * \sigma_y}{\sigma_x} $$ $$ slope = \frac{r * \sigma_y}{\sigma_x} $$
#### Residual plots #### Residual plots