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MAINT: remove %matplotlib inline and remove contents directives #26

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Jun 13, 2024
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MAINT: remove %matplotlib inline and remove contents directives #26

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4 changes: 0 additions & 4 deletions lectures/exchangeable.md
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# Exchangeability and Bayesian Updating

```{contents} Contents
:depth: 2
```

## Overview

This lecture studies learning
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4 changes: 0 additions & 4 deletions lectures/imp_sample.md
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Expand Up @@ -13,10 +13,6 @@ kernelspec:

# Computing Mean of a Likelihood Ratio Process

```{contents} Contents
:depth: 2
```

## Overview

In {doc}`this lecture <likelihood_ratio_process>` we described a peculiar property of a likelihood ratio process, namely, that it's mean equals one for all $t \geq 0$ despite it's converging to zero almost surely.
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5 changes: 0 additions & 5 deletions lectures/likelihood_ratio_process.md
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# Likelihood Ratio Processes

```{contents} Contents
:depth: 2
```


## Overview

This lecture describes likelihood ratio processes and some of their uses.
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4 changes: 0 additions & 4 deletions lectures/lln_clt.md
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```{index} single: Central Limit Theorem
```

```{contents} Contents
:depth: 2
```

## Overview

This lecture illustrates two of the most important theorems of probability and statistics: The
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4 changes: 0 additions & 4 deletions lectures/mle.md
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# Maximum Likelihood Estimation

```{contents} Contents
:depth: 2
```

## Overview

In a {doc}`previous lecture <ols>`, we estimated the relationship between
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4 changes: 0 additions & 4 deletions lectures/multi_hyper.md
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# Multivariate Hypergeometric Distribution

```{contents} Contents
:depth: 2
```

## Overview

This lecture describes how an administrator deployed a **multivariate hypergeometric distribution** in order to access the fairness of a procedure for awarding research grants.
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4 changes: 0 additions & 4 deletions lectures/multivariate_normal.md
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# Multivariate Normal Distribution

```{contents} Contents
:depth: 2
```

## Overview

This lecture describes a workhorse in probability theory, statistics, and economics, namely,
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4 changes: 0 additions & 4 deletions lectures/navy_captain.md
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# Bayesian versus Frequentist Decision Rules

```{contents} Contents
:depth: 2
```

In addition to what's in Anaconda, this lecture will need the following libraries:

```{code-cell} ipython
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4 changes: 0 additions & 4 deletions lectures/ols.md
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# Linear Regression in Python

```{contents} Contents
:depth: 2
```

In addition to what's in Anaconda, this lecture will need the following libraries:

```{code-cell} ipython
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4 changes: 0 additions & 4 deletions lectures/prob_matrix.md
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Expand Up @@ -1320,8 +1320,6 @@ x_mesh, y_mesh = np.meshgrid(x, y, indexing="ij")
Let's plot the **population** joint density.

```{code-cell} ipython3
# %matplotlib notebook

fig = plt.figure()
ax = plt.axes(projection='3d')

Expand All @@ -1330,8 +1328,6 @@ plt.show()
```

```{code-cell} ipython3
# %matplotlib notebook

fig = plt.figure()
ax = plt.axes(projection='3d')

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4 changes: 0 additions & 4 deletions lectures/troubleshooting.md
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# Troubleshooting

```{contents} Contents
:depth: 2
```

This page is for readers experiencing errors when running the code from the lectures.

## Fixing Your Local Environment
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4 changes: 0 additions & 4 deletions lectures/wald_friedman.md
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```{index} single: Models; Sequential analysis
```

```{contents} Contents
:depth: 2
```

In addition to what's in Anaconda, this lecture will need the following libraries:

```{code-cell} ipython3
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