Regression tutorials (#1195) (#1195)

Summary:
allow-large-files

### Motivation
Tutorial improvements for OSS release

### Changes proposed
* Merges robust and ordinary linear regression tutorials
* Cleans up robust regression to run without errors

Pull Request resolved: #1195

Pull Request resolved: #1276

Test Plan:
Manual review

### Types of changes
- [x] Docs change / refactoring / dependency upgrade
- [x] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to change)

### Checklist
- [x] My code follows the code style of this project.
- [x] My change requires a change to the documentation.
- [x] I have updated the documentation accordingly.
- [x] I have read the **[CONTRIBUTING](https://github.com/facebookincubator/BeanMachine/blob/master/CONTRIBUTING.md)** document.
- [ ] I have added tests to cover my changes.
- [ ] All new and existing tests passed.
- [x] The title of my pull request is a short description of the requested changes.

**Static Docs Preview: beanmachine**
|[Full Site](https://our.intern.facebook.com/intern/staticdocs/eph/D33124449/V5/beanmachine/)|

|**Modified Pages**|
|[docs/tutorials](https://our.intern.facebook.com/intern/staticdocs/eph/D33124449/V5/beanmachine/docs/tutorials/)|
Please provide clear instructions on how the changes were verified. Attach screenshots if applicable.

### Types of changes
- [ ] Docs change / refactoring / dependency upgrade
- [ ] Bug fix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to change)

### Checklist
- [ ] My code follows the code style of this project.
- [ ] My change requires a change to the documentation.
- [ ] I have updated the documentation accordingly.
- [ ] I have read the **[CONTRIBUTING](https://github.com/facebookresearch/beanmachine/blob/main/CONTRIBUTING.md)** document.
- [ ] I have added tests to cover my changes.
- [ ] All new and existing tests passed.
- [ ] The title of my pull request is a short description of the requested changes.

Reviewed By: neerajprad

Differential Revision: D33124449

Pulled By: feynmanliang

fbshipit-source-id: 2a02cb073d87e7959e3c05ffc199e3a6bab8921b

docs/overview/tutorials/tutorials.md

@@ -20,6 +20,12 @@ This tutorial demonstrates modeling and running inference on a simple coin-flipp
 
 This tutorial demonstrates modeling and running inference on a simple univariate linear regression model in Bean Machine. This should offer an accessible introduction to models that use PyTorch tensors and Newtonian Monte Carlo inference in Bean Machine. It will also teach you effective practices for prediction on new datasets with Bean Machine.
 
+### Robust Linear Regression
+
+[Open in GitHub](https://github.com/facebookresearch/beanmachine/blob/master/tutorials/Robust_Linear_Regression.ipynb) • [Run in Google Colab](https://colab.research.google.com/github/facebookresearch/beanmachine/blob/master/tutorials/Robust_Linear_Regression.ipynb)
+
+This tutorial illustrates a robust extension to the Linear Regression tutorial. A similar setup is employed except here the dataset is explicitly corrupted through the addition of outliers. You will learn how to modify the model such that correct inferences are recovered despite the presence of outliers.
+
 
 ### Logistic Regression
 

src/beanmachine/ppl/diagnostics/common_statistics.py

@@ -29,7 +29,7 @@ def std(query_samples: Tensor) -> Tensor:
 def confidence_interval(query_samples: Tensor) -> Tensor:
     percentile_list = [2.5, 50, 97.5]
     query_dim = query_samples.shape[2:]
-    query_samples = query_samples.view(-1, *query_dim)
+    query_samples = query_samples.reshape(-1, *query_dim)
     return torch.tensor(
         np.percentile(query_samples.detach().numpy(), percentile_list, axis=0)
     )