An answer to your second question:
Random number generated by your computer are not truly random, they are pseduo
random meaning that if your computer is it the exact same state at two
movements, it will produce the same string of "random" numbers. Set.seed
effectively puts your machine in a given state - it primes the pseudo random
number generator. If you set the seed before requesting a set of random
numbers, you will always get the same set of numbers. If you don't use
set.seed, the machine primes the generator using some other source, which may
be the system clock. Thus, if you don't use set.seed, it would be very, very,
unlikely that you would get the same string of random numbers.
John
John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)>>> Amelia
Livington <amelia_living...@yahoo.com> 12/23/2009 6:24 AM >>>
Hi!
Suppose I have a dataset as follows
pd = c(10,7,10,11,7,11,7,6,8,3,12,7,7,10,10)
I wish to calculate the mean, standard deviation, median, skewness and kurtosis
i.e. regular standard statistical measures.
average = mean(pd)
stdev = sd(pd)
median = median(pd)
skew = skewness(pd)
kurt = kurtosis(pd)
Q. No (1)
How do I get these at a stretch using some R package? I came across moments and
e1071 package, but I am not sure which one to use and how?
Q. No. (2)
Many times I came across the command
set.seed(1234)
What is the significance of this command. I understand this is related to
random number generation. But what does it do?
Thanking in advance
Amelia
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