Precision - or lack there of

Indeed, you are correct! In never pays to do stats too early in the
morning!
John

John Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
Baltimore VA Medical Center GRECC,
University of Maryland School of Medicine Claude D. Pepper OAIC,
University of Maryland Clinical Nutrition Research Unit, and
Baltimore VA Center Stroke of Excellence

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)
jsorkin at grecc.umaryland.edu

Peter Dalgaard <p.dalgaard at biostat.ku.dk> 12/9/2006 9:41 AM >>>

R 2.3.1
Windows XP 

I am surprised at the lack of precision in R, as noted below. I

would

expect the values to be closer to zero, particularly the later

examples

where the sample size is quite large.

  

mean(rnorm(500,0,1))
    

[1] -0.03209727
  

mean(rnorm(5000,0,1))
    

[1] -0.005991322
  

mean(rnorm(50000,0,1))
    

[1] -0.0006160524
  

mean(rnorm(500000,0,1))
    

[1] -0.001254309
  

mean(rnorm(5000000,0,1))
    

[1] 0.0004633778
  

mean(rnorm(50000000,0,1))
    

[1] -0.0001325764

I would appreciate any thoughts. Is the lack of precision due to
running on a 32-bit system?

Thanks,
John


J

Looks OK to me. The theoretical SEM in the latter case is 
sqrt(1/5e7)==0.0001414214.

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