# spearman.plot: Spearman plot In fifer: A Biostatisticians Toolbox for Various Activities, Including Plotting, Data Cleanup, and Data Analysis

## Description

Plots the relationship between two variables using a Spearman Plot

## Usage

 ```1 2``` ```spearman.plot(x, y = NULL, dcol = "blue", lhist = 20, num.dnorm = 5 * lhist, plot.cor = TRUE, ...) ```

## Arguments

 `x` either a matrix with two columns or a vector (if y is not `NULL`) `y` a vector `dcol` the color of the lines drawn for the density plot `lhist` the number of breaks in the histogram `num.dnorm` the number of breaks in the density line `plot.cor` logical. Should the spearman correlation be outputted in the plot? `...` arguments passed to `plot`

## Details

Often data are not normally distributed, requiring the use of a spearman correlation to determine their relationship. However, doing so makes it difficult to visualize the data since scatterplots of raw data present the data as if a pearson correlation were used. This function plots the ranks of the data, while plotting along the axes the distributions of the raw data.

Dustin Fife

## Examples

 ```1 2 3 4 5 6``` ```### generate skewed data x = rnorm(1000)^2 y = .6*x + rnorm(1000, 0, sqrt(1-.6^2)) spearman.plot(cbind(x,y), col="red", lhist=50) spearman.plot(x=iris\$Sepal.Length, y=iris\$Sepal.Width) ```

fifer documentation built on May 30, 2017, 7:40 a.m.