Creating graphs in Stata
===============================================================
Below we review some diagnostic plots available in Stata, and we demonstrate
how to overlay plots. We use `auto.dta`, which contains pricing and mileage
data for 1978 automobiles.
---

<!--- In the previous example, we used three back-ticks for a block of code.
Here we use a single back-tick for inline code. -->

## Plotting predictions
We are interested in modeling the mean of **mpg**, miles per gallon, as a function of **weight**, car weight in pounds. We can use **twoway lfitci** to graph the predicted miles per gallon from a linear regression, as well as the confidence interval:

```
 sysuse auto, clear
 twoway lfitci mpg weight
```
To see how these predictions compare to our data, we can overlay a scatterplot
of the actual data

```
twoway lfitci mpg weight || scatter mpg weight, title(MPG as a function of weight)
```
which produces the following graph:

![Graph of mpg](mpg1.png)
<!--- We previously used **graph export** to save the graph as a .png file, which we now embed in the document. -->

We could have also created separate graphs for domestic and foreign
cars with the **by()** option. See
[graph twoway lfitci](https://www.stata.com/manuals/g-2graphtwowaylfitci.pdf)
 in the Stata Graphics Reference Manual for details.
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## Diagnostic plot
There are multiple diagnostic plots available for use after **regress**. Here,
we use **rvfplot** to graphically check for a relationship between the
residuals and fitted values from our model. We regress **mpg** on
**weight** and then issue **rvfplot**.
```
regress mpg weight
rvfplot, yline(0) title(Residuals versus fitted values)
```
The commands above produce the following graph:

![Diagnostic plot](diagplot.png)

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