Description Usage Arguments Value Author(s) References Examples
Performs the Shapiro-Wilks test for normality on a set of residuals from an analysis. This is a wrapper function for the shapiro.test
function with additional evaluation statistics.
1 | wilksTest(Residuals)
|
Residuals |
Residuals from an analysis. |
WilksTest, a data frame containing:
OBS |
Total number of observation. |
STD |
The standard error. |
SKEW |
The skew of the data set. |
KURT |
The measure of kurtosis (how heavy tailed the distribution is) of the data set. |
SW_STAT |
The Shapiro-Wilks test statistic. |
P_VALUE |
The p-Value for the test statistic. |
Signif |
The flag for p-values less then 0.01. |
Joe Swintek
Patrick Royston (1982) An extension of Shapiro and Wilk's W test for normality to large samples. Applied Statistics, 31: 115-124.
Patrick Royston (1982) Algorithm AS 181: The W test for Normality. Applied Statistics, 31: 176-180.
Patrick Royston (1995) Remark AS R94: A remark on Algorithm AS 181: The W test for normality. Applied Statistics, 44: 547-551.
Johnson, NL, Kotz, S, Balakrishnan N (1994) Continuous Univariate Distributions, Vol 1, 2nd Edition Wiley ISBN 0-471-58495-9.
1 2 3 4 5 6 7 8 9 | #Data
data(lengthWeightData)
#Subset the data
SubData<-lengthWeightData[lengthWeightData$Age=='16 week', ]
SubData<-SubData[SubData$Generation=='F1', ]
SubData<-SubData[SubData$SEX=='M', ]
#Run
Residuals<-aov(WEIGHT~Treatment,SubData)$residuals
wilksTest(Residuals)
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