Height-Weight Covariance Study
The data set highlights the importance of handling covariance when such information is available. If the covariance is not incorporated, hypothesis testing may lead to entirely difference conclusion.
data(hw)
A data frame with 20 observations on the following 2 variables.
Heightthe height of an individual
Weightthe weight of an individual
Rencher, A.C. (2002). Methods of Multivariate Analysis, 2e. J. Wiley.
data(hw) sigma0 <- matrix(c(20, 100, 100, 1000),nrow=2) sigma <- var(hw) v <- nrow(hw)-1 p <- ncol(hw) u <- v*(log(det(sigma0))-log(det(sigma)) + sum(diag(sigma%*%solve(sigma0)))-p) u1 <- (1- (1/(6*v-1))*(2*p+1 - 2/(p+1)))*u u;u1;qchisq(1-0.05,p*(p+1)/2)
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