This returns a list of different multivariate normality tests. I chose the Shapiro–Wilk test (Shapiro & Wilk, 1965) because it is the most powerful in detecting departures from normality (Razali & Wah, 2011; Stevens, 2009, p. 223). For example, the R package mvnormtest is listed, which has a function mshapiro.test(), for the Shapiro–Wilk multivariate normality test. The argument that needs to be supplied in the function is the U value, which represents a transposed numeric matrix of data values ranging from 3 to 5,000. There are a few simple steps required before running the R function: