Compare distribution of data with normal distribution.
Compare distribution of data with normal distribution.
check_normaldist( res, col = "red", col.normal = "black", legend.pos = "topright", legend.label = "data", ... )
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
|
legend.label |
Text string, label for plotted data distribution. |
... |
Optional arguments for the lines. See |
Assumes centered data as input.
Jacolien van Rij
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()
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)
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