# Purpose

`nhstplot` is a simple and convenient package to represent graphically the most common Null Hypothesis Significance Tests (NHST).

One plot being worth 1000 words, it does this...

With a very minimal amount of (intuitive) coding (here `plotftest(f = 4, dfnum = 3, dfdenom = 5)`, and even `plotftest(4,3,5)` works the same if you're in a hurry).

In other words, it plots the density functions of (z), (t), (F) and (^2), adding a cutline at the observed statistic value, scaling it all conveniently, and plotting a label for the (p) value.

# How to use it

First, install the library with `install.packages("nhstplot")`

``library(nhstplot)``

## Basic functions

'nhstplot' is composed of 4 functions, one for each major NHST test "family" :

• (^2) tests (with the `plotchisqtest` function)
• (F) tests (with the `plotftest` function)
• (t) tests (with the `plotttest` function)
• (z) tests (with the `plotztest` function)

They all work quite the same (with minor differences, see the vignette for more info), with very few required arguments:

• The first required argument is the value of the test statistic (z), (t), (F) and (^2)
• The other required arguments are the degrees of freedom (except for (z) of course)

That's it.

## One tailed tests

`nhstplot`is very flexible, but its strength is its helpful defaults and easy options.

For example, by default, when appropriate, two-tailed (z) and (t) tests are performed, but just add `tails = "one"` to get a one-tailed test that adapts to the sign of the test statistics:

``plotttest(-2, 10, tails = "one")``
``plotttest(2, 10, tails = "one")``

## "Blanking"

To explain NHST in successive steps (and look good doing it), you may be tempted to "blank the plot" with `blank = TRUE`, which outputs the exact same graphs as before, but without the "cutting" part:

``plotztest(1, blank = TRUE)``

It's especially useful for any "step-by-step" explanation.

## Colors

And finally, if you don't like the default theme, I've added others, that can be called with `theme`, that can probably accomodate you (see the documentation or vignette for a list).

``plotztest(1, theme = "blackandwhite")``
``plotztest(1, theme = "whiteandred")``

There are other options. See the vignette for further customizations.

## Disclaimer

This package is neither for or against NHST. It's meant to help explain the process, should you want to explain it. A lot of students (and scholars) have no choice but to read articles with (p) values, so they might as well have a better understanding of what it is and what it's not anyway, right?

## Bug reports

I will try to implement new features soon, so check that you have the newest version.