get_visual_fusion_data = function(){
    ##
    ## Raw data from: xpdf ../EBook/Applied_Linear_Models_with_R.pdf -z 200 69 &
    ##
    nv = c(47.2, 22.0, 20.4, 19.7, 17.4, 14.7, 13.4, 13.0, 12.3, 12.2, 10.3, 9.7, 9.7, 9.5, 9.1, 8.9, 8.9, 8.4, 8.1, 7.9, 7.8, 6.9, 6.3, 6.1, 5.6, 4.7, 4.7, 4.3, 4.2, 3.9, 3.4, 3.1, 3.1, 2.7, 2.4, 2.3, 2.3, 2.1, 2.1, 2.0, 1.9, 1.7, 1.7)
    vv = c(19.7, 16.2, 15.9, 15.4, 9.7, 8.9, 8.6, 8.6, 7.4, 6.3, 6.1, 6.0, 6.0, 5.9, 4.9, 4.6, 3.8, 3.6, 3.5, 3.3, 3.3, 2.9, 2.8, 2.7, 2.4, 2.3, 2.0, 1.8, 1.7, 1.7, 1.6, 1.4, 1.2, 1.1, 1.0)

    nv_str = rep('NV', length(nv) )
    vv_str = rep('VV', length(vv) )

    fusion = data.frame(Time=c(nv, vv), Treatment=c(nv_str, vv_str))
    fusion$Treatment = as.factor(fusion$Treatment)
    
    return(fusion)
}