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notebooks/01a-Instructor-Probability_a_simulated_introduction.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 1. Probability"
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"## Probability"
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]
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},
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {
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"toc-hr-collapsed": false
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},
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"source": [
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"## 2. Simulating probabilities"
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"## Simulating probabilities"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"### Hands-on: more clicking"
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"### Hands-on: clicking"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"### A proxy for probability\n",
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"### Proportion: A proxy for probability\n",
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"\n",
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"As stated above, we have calculated a proportion, not a probability. As a proxy for the probability, we can simulate drawing random samples (with replacement) from the data seeing how many lengths are > 10 and calculating the proportion (commonly referred to as [hacker statistics](https://speakerdeck.com/jakevdp/statistics-for-hackers)):"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Hands-on"
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"### Hands-on: Probabilities"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Empirical cumulative distribution functions (ECDFs)"
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"## Empirical cumulative distribution functions (ECDFs)"
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Hands-on"
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"### Hands-on: Plotting ECDFs"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 3. PROBABILITY DISTRIBUTIONS AND THEIR STORIES"
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"## Probability distributions and their stories"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Hands-on"
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"#### Hands-on: Poisson"
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]
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Example Poisson distribution: field goals attempted per game"
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"#### Example Poisson distribution: field goals attempted per game"
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]
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## HANDS ON"
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"#### Hands-on: Simulating Data Generating Stories"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exponential distribution"
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"### Exponential distribution"
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]
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## HANDS ON"
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"#### Hands-on: Simulating Normal"
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]
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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"version": "3.7.2"
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},
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"toc-autonumbering": true
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},
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"nbformat": 4,
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"nbformat_minor": 2

notebooks/01b-Instructor-Probability_a_simulated_introduction.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 1. Joint Probability & Conditional Probability"
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"## Joint Probability & Conditional Probability"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### HANDS-ON: JOINT PROBABILITY COIN FLIPPING"
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"#### Hands-On: Joint Probability and Coin Flipping"
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"cell_type": "markdown",
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"metadata": {},
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"### HANDS-ON: joint probability for birds"
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"#### Hands-On: Joint probability for birds"
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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"version": "3.7.2"
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}
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},
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"nbformat": 4,

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