# Scatterplots

This is an early work-in-progress.

We can make simple scatterplots using the general `plot` function. We use the vector of x values as the first parameter and the vector of y values as the second parameter. Generally,

```plot(`explanatory`, `response`)
```

Here are some examples. (Of course, you'll generally get those values from an existing data set.)

```plot(c(1,2,4,5,5,7,10,11), c(2,3,4,3,5,6,7,8))
plot(c(1,2,2,3,3,3,4,4,5), c(1,5,10,2,6,11,3,7,12))
```

You can also join the two vectors together with the `~` operation, in which case the code will look something like

```plot(`response` ~ `explanatory`)
```

We'll tend to use whichever of these forms is most convenient at the moment.

## An Alternative

The `car` library provides somewhat more elegant scatterplots, with the regression line and some box-and-whiskers plots added. To use that library, you need to load it first.

```library(car, lib="/home/rebelsky/Stats115/Packages")
```

If you're working on your own computer, you need to install your own copy of that library.

```install.package("car")
```

Once you've loaded that library, you can make scatterplots with the `scatterplot` function. Typically, the first parameter is a vector of X values and the second parameter is a vector of Y values.

```scatterplot(c(1,2,4,5,5,7,10,11), c(2,3,4,3,5,6,7,8))
scatterplot(c(1,2,2,3,3,3,4,4,5), c(1,5,10,2,6,11,3,7,12))
```

If you don't want to see the funky curve that attempts to show a best approximation, add `smooth=FALSE`.

If you don't want to see the regression line, add `reg.line=FALSE`.

Samuel A. Rebelsky, rebelsky@grinnell.edu

Copyright (c) 2007-8 Samuel A. Rebelsky.

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