Whether it is about death, coma, or certain extreme events, these are all predictable, though not with probability one, but with much higher probability one can think of.
Why i think Michael Jackson’s death, a shock to the world, a sad news from the king of pop and the guy who really made the possibility of suppressed segment of the society to come to the top (along with Mohammed Ali, President Obama, and Tiger Woods) is predictable, with high degree of probability.
– Michael Jackson is under extreme social pressure (social dark sides as some commentators call it, serious credit leveraging – current loans, mostly lonely, drug addiction, previous cardiac related difficulties) – wow, a very convincing line of factors.
– Yet it was a shock for me to hear the news
– May it is just the wish that he did not die that was not willing to accept the high likelihood of the event
Use the commands (to get side by side bar charts for two vectors in R; note how to get the labels for each chart and also how to print vector values over the bars)
x barplot(height,beside=T,main=”Cluster Distributions”,xlab=”Clusters”, ylab=”Percentages”, names=labels,col=c(“violet”,”beige”))
# Draw the bar values above the bars
> text(mp, height, labels = format(height, 4), pos = 3, cex = .75, col=c(“blue”,”red”))
Check what happens when beside=T is removed. After the first iteration, it became clear that i have to seperate out the first cluster (all people who do not have chronic disease), the rest of the clusters are all who have chronic diseases and co-morbid disease combinations.