## Usage

normalityAssessment(sampleVector, samples = 10000, digits=2, samplingDistColor = "#2222CC", normalColor = "#00CC00", samplingDistLineSize = 2, normalLineSize = 1, xLabel.sampleDist = NULL, yLabel.sampleDist = NULL, xLabel.samplingDist = NULL, yLabel.samplingDist = NULL, sampleSizeOverride = TRUE)
samplingDistribution(popValues = c(0, 1), popFrequencies = c(50, 50), sampleSize = NULL, sampleFromPop = FALSE, ...)
dataShape(sampleVector, na.rm = TRUE, type = 2, digits = 2, conf.level = 0.95, plots = TRUE, xLabs = NA, yLabs = NA, qqCI = TRUE, labelOutliers = TRUE, sampleSizeOverride = NULL)

## Arguments

sampleVector

Numeric vector containing the sample data.

samples

Number of samples to use when constructing sampling distribution.

digits

Number of digits to use when printing results.

samplingDistColor

Color to use when drawing the sampling distribution.

normalColor

Color to use when drawing the standard normal curve.

samplingDistLineSize

Size of the line used to draw the sampling distribution.

normalLineSize

Size of the line used to draw the standard normal distribution.

xLabel.sampleDist

Label of x axis of the distribution of the sample.

yLabel.sampleDist

Label of y axis of the distribution of the sample.

xLabel.samplingDist

Label of x axis of the sampling distribution.

yLabel.samplingDist

Label of y axis of the sampling distribution.

xLabs, yLabs

The axis labels for the three plots (should be vectors of three elements; the first specifies the X or Y axis label for the rightmost plot (the histogram), the second for the middle plot (the QQ plot), and the third for the rightmost plot (the box plot).

popValues

The possible values (levels) of the relevant variable. For example, for a dichotomous variable, this can be "c(1:2)" (or "c(1, 2)"). Note that samplingDistribution is for manually specifying the frequency distribution (or proportions); if you have a vector with 'raw' data, just call normalityAssessment directly.

popFrequencies

The frequencies corresponding to each value in popValues; must be in the same order! See the examples.

sampleSize

Size of the sample; the sum of the frequencies if not specified.

na.rm

Whether to remove missing data first.

type

Type of skewness and kurtosis to compute; either 1 (g1 and g2), 2 (G1 and G2), or 3 (b1 and b2). See Joanes & Gill (1998) for more information.

conf.level

Confidence of confidence intervals.

plots

Whether to display plots.

qqCI

Whether to show the confidence interval for the QQ plot.

labelOutliers

Whether to label outliers with their row number in the box plot.

sampleFromPop

If true, the sample vector is created by sampling from the population information specified;
if false, rep() is used to generate the sample vector. Note that is proportions are
supplied in popFrequencies, sampling from the population is necessary!

sampleSizeOverride

Whether to use the sample size of the sample as sample size for the sampling distribution,
instead of the sampling distribution size. This makes sense, because otherwise, the sample
size and thus sensitivity of the null hypothesis significance tests is a function of the
number of samples used to generate the sampling distribution.

...

Anything else is passed on my sampingDistribution to normalityAssessment.