From 1bd9020f269e1f86cb539fb8e9b3b349bf31806d Mon Sep 17 00:00:00 2001 From: Jan Kirenz <48259550+kirenz@users.noreply.github.com> Date: Sat, 11 Nov 2023 11:03:51 +0100 Subject: [PATCH] Update index.qmd --- index.qmd | 37 ++++++++++++++++++++++++++----------- 1 file changed, 26 insertions(+), 11 deletions(-) diff --git a/index.qmd b/index.qmd index 6f22056..3037030 100644 --- a/index.qmd +++ b/index.qmd @@ -54,14 +54,29 @@ Welcome to our course Data Analytics with Statistics! 👋 | 40 | **Linear Regression models** | | | | | | | 41 | Correlation | [📚](https://openintro-ims.netlify.app/model-slr.html#describing-linear-relationships-with-correlation) | [📑](https://docs.google.com/presentation/d/1JyvtQBRiUhjncLki3ozy4SvvgwRqS7Gmj_vUpFokzzo/export/pdf) | [☑️](https://forms.gle/5ntV6z8yHk8g4qgZ8) | | | | 42 | Sales and ads | | [📑](https://docs.google.com/presentation/d/1q9o_PycjwItr-5PxotZFFzkwdqvo8fVskv_Y0H1CbxE/export/pdf) | | | | -| 43 | Mean squared error | | [📑](https://docs.google.com/presentation/d/1DnX0RnGCguOE2elQJFrcu2efZp6hjre7fsTrAfBJQTA/export/pdf) | | | | -| 44 | Fitting a line and residuals | [📚](https://openintro-ims.netlify.app/model-slr.html#fit-line-res-cor) | [📑](https://docs.google.com/presentation/d/18xWbx5rkptYfOaqzpfIc7RD-LC9Y-Wgs_7tz9Z2a2hg/export/pdf) | [☑️](https://forms.gle/JFMXzjByDRGZtbDx8) | | | -| 45 | Least squares regression | [📚](https://openintro-ims.netlify.app/model-slr.html#least-squares-regression) | [📑](https://docs.google.com/presentation/d/1jreIuC0fOiVPHt6CUNYb-Kb4uKogCeftBZP5Zum6jSQ/export/pdf) | | | | -| 46 | R squared | [📚](https://openintro-ims.netlify.app/model-slr.html#r-squared) | | | | | -| 47 | Categorical predictors with two levels | [📚](https://openintro-ims.netlify.app/model-slr.html#categorical-predictor-two-levels) | | | | | -| 48 | Outliers | [📚](https://openintro-ims.netlify.app/model-slr.html#outliers-in-regression) | | | | | -| 49 | Multiple predictors regression 1 | [📚](https://openintro-ims.netlify.app/model-mlr.html#model-mlr) | | [☑️](https://forms.gle/wHPHMvbTDczNaQD97) | | | -| 50 | Multiple predictors regression 2 | | | | | | -| 51 | Multiple predictors regression 3 | | | | | | -| 52 | **Linear Regression with Data Splitting** | | | | | | -| 53 | Regression example happier | | | | | | \ No newline at end of file +| 43 | Mean squared error | | [📑](https://docs.google.com/presentation/d/1DnX0RnGCguOE2elQJFrcu2efZp6hjre7fsTrAfBJQTA/export/pdf) | | | | +| 44 | Fitting a line and residuals | [📚](https://openintro-ims.netlify.app/model-slr.html#fit-line-res-cor) | [📑](https://docs.google.com/presentation/d/18xWbx5rkptYfOaqzpfIc7RD-LC9Y-Wgs_7tz9Z2a2hg/export/pdf) | [☑️](https://forms.gle/JFMXzjByDRGZtbDx8) | | | +| 45 | Least squares regression | [📚](https://openintro-ims.netlify.app/model-slr.html#least-squares-regression) | [📑](https://docs.google.com/presentation/d/1jreIuC0fOiVPHt6CUNYb-Kb4uKogCeftBZP5Zum6jSQ/export/pdf) | | | | +| 46 | R squared | [📚](https://openintro-ims.netlify.app/model-slr.html#r-squared) | | | | | +| 47 | Categorical predictors with two levels | [📚](https://openintro-ims.netlify.app/model-slr.html#categorical-predictor-two-levels) | | | | | +| 48 | Outliers | [📚](https://openintro-ims.netlify.app/model-slr.html#outliers-in-regression) | | | | | +| 49 | Multiple predictors regression 1 | [📚](https://openintro-ims.netlify.app/model-mlr.html#model-mlr) | | [☑️](https://forms.gle/wHPHMvbTDczNaQD97) | [💻](https://colab.research.google.com/github/kirenz/lab-ims/blob/main/ims/08a-1-multiple.ipynb) | | +| 50 | Multiple predictors regression 2 | | | | [💻](https://colab.research.google.com/github/kirenz/lab-ims/blob/main/ims/08a-2-multiple.ipynb) | | +| 51 | Multiple predictors regression 3 | | | | [💻](https://colab.research.google.com/github/kirenz/lab-ims/blob/main/ims/08a-3-multiple.ipynb) | | +| 52 | **Linear Regression with Data Splitting** | | | | | | +| 53 | Regression example happier | | | | [💻](https://colab.research.google.com/github/kirenz/lab-models/blob/main/mr/happier-c.ipynb) | | +| 54 | Main model challenges | [📚](https://e-learning.hdm-stuttgart.de/moodle/pluginfile.php/430097/mod_resource/content/0/Hands%20on%20Machine%20Learning%2C%20Model%20Challenges.pdf) | | | | | +| 55 | Data splitting | | | | [💻](https://colab.research.google.com/github/kirenz/lab-models/blob/main/mr/happier-splitting-c.ipynb) | | +| 56 | Sales prediction | | | | [💻](https://colab.research.google.com/github/kirenz/lab-altair/blob/main/ae/04-2-stacked-bar-chart-altair.ipynb) | | +| 57 | Sales prediction with data splitting | | | | [💻](https://colab.research.google.com/github/kirenz/lab-altair/blob/main/ae/04-2-standardized-bar-chart-altair.ipynb) | | +| 58 | **Advanced Linear Regression models** | | | | | | +| 59 | Regression splines | [📚](https://www.statlearning.com/) | | | | | +| 60 | Generalized additive models | [📚](https://www.statlearning.com/) | | | | | +| 61 | Adjusted R squared | [📚](https://openintro-ims.netlify.app/model-mlr.html#adjusted-r-squared) | | | | | +| 62 | Regression diagnostics | | | | | | +| 63 | **Model Selection Methods** | | | | | | +| 64 | Model selection methods | [📚](http://www.feat.engineering/selection.html) | | | | | +| 65 | Implicit model selection | [📚](https://www.statlearning.com/) | | | [💻](https://colab.research.google.com/github/kirenz/lab-ims/blob/main/ims/08d-1-implicit.ipynb) | | +| 66 | Lasso regression | [📚](https://www.statlearning.com/) | | | [💻](https://colab.research.google.com/github/kirenz/notebooks/blob/main/ims/copy/99-1-lasso-c.ipynb) | | +| 67 | Filter model selection | [📚](http://www.feat.engineering/selection.html) | | | [💻](https://colab.research.google.com/github/kirenz/lab-ims/blob/main/ims/08d-2-filter.ipynb) | | +| 68 | Wrapper model selection | [📚](http://www.feat.engineering/selection.html) | | | [💻](https://colab.research.google.com/github/kirenz/lab-ims/blob/main/ims/08d-3-wrapper.ipynb) | | \ No newline at end of file