check_normaldist: Compare distribution of data with normal distribution.

In plotfunctions: Various Functions to Facilitate Visualization of Data and Analysis

Description

Compare distribution of data with normal distribution.

Usage

check_normaldist(
  res,
  col = "red",
  col.normal = "black",
  legend.pos = "topright",
  legend.label = "data",
  ...
)

Arguments

res	Vector with residuals or other data for which the distribution .
col	Color for filling the area. Default is black.
col.normal	Color for shading and line of normal distribution.
legend.pos	Position of legend, can be string (e.g., 'topleft') or an xy.coords object.
legend.label	Text string, label for plotted data distribution.
...	Optional arguments for the lines. See par.

Note

Assumes centered data as input.

Author(s)

Jacolien van Rij

See Also

Other Functions for plotting: addInterval(), add_bars(), add_n_points(), alphaPalette(), alpha(), color_contour(), dotplot_error(), drawDevArrows(), emptyPlot(), errorBars(), fill_area(), getCoords(), getFigCoords(), getProps(), gradientLegend(), legend_margin(), marginDensityPlot(), plot_error(), plot_image(), plotsurface(), sortBoxplot()

Examples

set.seed(123)
# normal distribution:
test <- rnorm(1000)
check_normaldist(test)
# t-distribution:
test <- rt(1000, df=5)
check_normaldist(test)
# skewed data, e.g., reaction times:
test <- exp(rnorm(1000, mean=.500, sd=.25))
check_normaldist(test)
# center first:
check_normaldist(scale(test))
# binomial distribution:
test <- rbinom(1000, 1, .3)
check_normaldist(test)
# count data:
test <- rbinom(1000, 100, .3)
check_normaldist(test)

Example output

plotfunctions documentation built on April 28, 2020, 5:10 p.m.