# Walkthrough: A simple analysis using the Draw command, part 2 
**(10 minutes)**

Instead of just plotting a single variable, let's try plotting two
variables at once:

    [] tree1->Draw("ebeam:px")

:::{note}
This is a scatterplot, a handy way of observing the correlations between
two variables. The `Draw` command interprets the variables as
("y:x") to decide which axes to use.

It's easy to fall into the trap of thinking that each (x,y) point on a
scatterplot represents a pair of values in your n-tuple. The scatterplot
is a grid; each square in the grid is randomly populated with a density
of dots proportional to the number of values in that square.
:::

Try making scatterplots of different pairs of variables. Do you see any
correlations?

:::{note}
If you see a shapeless blob on the scatterplot, the variables are likely
to be uncorrelated; for example, plot **`px`** versus **`py`**. If you see a
pattern, there may be a correlation; for example, plot **`pz`** versus
`zv`. It appears that the higher **`pz`** is, the lower **`zv`** is, and
vice versa. Perhaps the particle loses energy before it is deflected in
the target.
:::

Let's create a "cut" (a limit on the range of a variable):

    [] tree1->Draw("zv","zv<20")

Look at the x-axis of the histogram. Compare this with:

    [] tree1->Draw("zv")

:::{note}
Note that ROOT determines {ref}`an appropriate range <autobin>` for the x-axis of your
histogram. Enjoy this while you can; this
feature is lost when you start using analysis macros.
:::

A variable in a cut does not have to be one of the variables you're
plotting:

    [] tree1->Draw("ebeam","zv<20")

Try this with some of the other variables in the tree.

The symbol for logical AND in C++ is "&&". Try using this in a cut,
e.g.:

    [] tree1->Draw("ebeam","px>10 && zv<20")