Introduction to Data Analysis with R

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<h1>Introduction to Data Analysis with R</h1>
<p>Lecture 6: Continuous Distributions, Statistics and PCA</p>
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Jannik Buhr
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<span>Heidelberg University, WS20/21</span>
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<div class="talk-date">2020-12-07</div>
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With Artwork by @allison_horst
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## Reproducible Environments with `renv`

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> »All models are wrong, but some are useful«
> — George Box

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## Types of Models

1. **Descriptive Models**
2. **Inferential Models** 
3. **Predictive Models**

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## Boxplots

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## Mean, Variance and SD

`$$var(X) = \frac{\sum_{i=0}^{n}{(x_i-\bar x)^2}}{(n-1)}$$`

`$$\sigma_X=\sqrt{var(X)}$$`

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## Standard Error of the Mean

`$$SEM=\sigma / \sqrt{n}$$`

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So the next time you see a barplot ask the question:

![[@ArtworkAllisonHorst]](img/summary_statistics.png){.external}

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## The t-distribution

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