# draw on pdf

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## How to draw on pdf

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### Supporting Forms

Submit important papers on the go with the number one online document management solution. Use our web-based app to edit your PDFs without effort. We provide our customers with an array of up-to-date tools accessible from any Internet-connected device. Upload your PDF document to the editor. Browse for a file on your device or add it from an online location. Insert text, images, fillable fields, add or remove pages, sign your PDFs electronically, all without leaving your desk.

### FAQ

How can I draw on a PDF file?
“$P(y|x)$ is Gaussian” simply means that given information about $x$, the random variable $y$ follows the Gaussian (a.k.a. normal) distribution. For example, consider the classic linear regression model $y = \alpha + \beta x + \epsilon$, where $\alpha$ and $\beta$ are constants, and $\epsilon$ is a normal random variable with mean 0 and standard deviation $\sigma_\epsilon$. Depending on what $x$ looks like, $P(y)$ may not be normal at all, but the distribution of $y$ given $x$ is precisely the normal distribution $P(y|x) = N[(\alpha + \beta x), \sigma_\epsilon]$.As for how you’d draw it … that’s not easy, really. You can draw the distribution of the residuals $\epsilon$ the same way you would anything else (histograms, density plots, etc.) and you’ll see a normal distribution. Or you could plot $y$ against $x$ and observe that the distribution of points about the line $y = \alpha + \beta x$ is approximately normal. But finding a good way to visualize conditional distributions in general is IMO an open challenge in visualization techniques. 