Hi Rolf, >> ... From the beginner's point of view it is useful to think of random >> variables ...
Who, exactly, is the beginner ? And was not Sir R. A. Fisher pretty arrogant and fractious ? He also was highly dismissive of Sir Richard Doll's conclusion that smoking caused cancer (himself being a smoker). Does that make him a bad statistician, or all statisticians "bad" or arrogant ? Regards, Mark. Rolf Turner-3 wrote: > > > On 5/03/2009, at 8:48 PM, Wacek Kusnierczyk wrote: > >> Rolf Turner wrote: >>> >>> Sports scores are random variables. You don't know a priori what the >>> scores are >>> going to be, do you? (Well, if you do, you must be able to make a >>> *lot* of money >>> betting on games!) After the game is over they aren't random any >>> more; they're >>> just numbers. But that applies to any random variable. A random >>> variable is >>> random only until it is observed, then POOF! it turns into a number. >>> >> >> may i respectfully disagree? >> >> to call for a reference, [1] says (p. 26, def. 1.4.1): >> >> a random variable is a function from sample space S into the real >> numbers. >> >> and it's a pretty standard definition. >> >> do you really turn a *function* into a *number* by *observing the >> function*? in the example above, you have a sample space, which >> consists of possible outcomes of a class of sports events. you have a >> random variable -- a function that maps from the number of goals into, >> well, the number of goals. >> >> after a sports event, the function is no less random, and no more a >> number. you have observed an event, you have computed one realization >> of the function (here's your number, which happens to be an >> integer) -- >> but the random variable does not turn to anything. >> >> vQ >> >> [1] Casella, Berger. Statistical Inference, 1st 1990 > > I was discussing the issue from an elementary/intuitive point of view. > The rigorous mathematical definition of a random variable as a > (measurable) > function from a sample (probability) space is not very helpful to the > beginner. > > From the beginner's point of view it is useful to think of random > variables > as being unpredictable quantities that you are *going* to observe. > After > you've observed them, you know what they are and prediction doesn't > come into > it; they are thus no longer random. > > From the more mathematical point of view the distinction is between the > function X : Omega |--> R (the real numbers), say, and a *particular > value* > of the function X(omega). > > In discussions of statistical inference the viewpoint is always shifting > backwards and forwards between the ``random sample'' X_1, ..., X_n and > the ``realized random sample'' x_1 = X_1(omega), ... x_n = X_n(omega). > Most students --- and I was one of them --- find this shifting point of > view confusing, and I think the elementary heuristic that I introduced > is helpful to many. > > cheers, > > Rolf > > ###################################################################### > Attention:\ This e-mail message is privileged and confid...{{dropped:9}} > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > -- View this message in context: http://www.nabble.com/Inference-for-R-Spam-tp22181352p22361224.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.