7/10    has anyone seen or knows the reason why I only see Mexicans
        picking up the trash in the office and vacuming hi-tech cos.?

7/11   http://www.theregister.co.uk/content/6/11779.html
       \_ great, now you can jack off with your nokia while driving to
          work.

7/10   What's wrong with this deal?:
       (SBC teaming with Prodigy to offer free compaq presario
       with DSL service).  Contract is for 2 years at $60/month
       for DSL.
        \_ It's normally $40/month.  Guess what you're paying extra for.

7/11    http://cbs.marketwatch.com/archive/20000207/news/current/superstar.htx?source=blq/yhoo&dist=yhoo

7/11    I currently get paid 93K in SV. I got an offer in NYC doing
        financial app for $130K. Is it a better deal considering a higher
        living standard there?
        \_ 93k?  That's it?  Doing what?
        \- cost of living != living standard. this is going to turn on
        what life style you want to some extent and not "can i live the same
        lifestyle for 35% more money". if you want more $, change jobs in the
        area. --psb
        \_ Also, have you ever lived in New York or spent an extended period
           of time there before?  People tend to be bipolar regarding the
           city-- either they fall in love with it or they hate it.  Who
           cares about the potential raise if you end up hating the city.
           -dans
           \_ Yep. You might end up to be a John Rocker.
                \_ who?
           \_ I agree with dans.  New York is a nice place to visit, but
              I would much rather live in SV than NY.  You should
              definetly spend some time in NY before you accept the job. -emin
              \_ thus demonstrating dans' argument.  i'd rather die than live
                 in silly valley, but i'd kill to live in ny.  with a proper
                 salary that is.  if you're poor its the worst place in the
                 universe.  -lye
        \_ I live in California because I hate NY.  -ex NYer
        \_ Seems like a good deal. Parts of Bay Area are already outgunning
           Manhattan rent-wise. Hate NYC myself though, nasty place. -muchandr

7/11    Hello nickkral!
        \_ Whoa, I'm famous.  -- nickkral
                \_ Try selling that.
        \_ hello nick kralevich, the deadbeat engineering buddy
               - i haven't forgotten you
        \_Who are you?!

7/11    What's a good formal measure of how well a distribution is approximated
        by a normal of the same mean and variance?
        \_ least squares?
        \_ Uh, the third moment, for starters.
           \_ How valid is this as a statistical measurement? I.e. if
              distr. A's skew is higher than distr. B's skew, is A expected
              to deviate from normal more than B on other parameters as well?
              \_ to see how bad this measure is, consider the distribution
                 delta(x) (which is infinity at 0 and 0 everywhere else)
                 and N(0,100) which is a zero mean gaussian with variance
                 100. the former is the narrowest distribution you'll find,
                 the former is very wide. yet their third moments are both 0.
                 a very bad measure indeed. in fact, all 0 mean even functions
                 have the same odd moments. -ali
                        \_ Life was much more pleasurable back in the old
                           days, when all I needed to go smack Rahimi's
                           pompous ass is going upstairs :) -muchandr
                 \_ This isn't applicable since I'm fixing the variance as
                    well. Of course the n+1'th moment is relatively useless
                    if the n'th moments are way off.
                    \_ the point is that if you have an even symmetric
                       zero mean distribution, the third moment will be
                       0, even if your second moments matches. You really
                       need to look at all moments to test for equality.
                       You should really look at mutual information (what
                       emin suggests) if don't have an application in mind
                       and just want a similarity measure with nice properties.
                       \_ noted, thx
        \_ You could also look at the Kullback-Leibler distance which is
           also known as relative entropy.  This has some nice properties.
           For example, if you build a Huffman code for distribution p
           and use it to compress a source with distribution q, the
           expected overhead for using the wrong distribution is D(p||q)
           where D(p||q) is relative entropy.  I don't remember the details
           but I think that D(p||q) also comes up if you are doing
           hypothesis testing where the true distribution is p but you
           think the distribution is q.  If you tell us what application
           you want a difference measure, we might be able to give better
           suggestions.  P.S., you could also using p-norms where
           p = 1,2, or infinity. -emin
           \_ I'm trying to do an approximate analysis of a hideously
              intractable numeric process, and this distribution, which
              is (graphically) "somewhat" normal looking is about half-way
              inside the bigger picture; since it's a sum over a bunch of
              binomial coefficients, I was advised to assume normality
              asymptotically to simplify things, but I want some way of
              getting a feel for how off I am. Yes, generic and not
              well-defined, but you really don't want to hear the gnarly
              details.
              \_ I'm not sure what you mean when you say "it's a sum over
                 a bunch of binomial coeffcients".  However, if you are
                 interested in the random variable S_n = (1/n)*sum(1,n) X_i
                 then the cdf of S_n will converge to a normal distribution
                 with a convergance rate roughly 1/sqrt(n) provided that
                 the random variables X_i are reasonably well behaved.
                 Lookup Central Limit Theorems for the details. -emin
                 \_ Noted; although I have some doubts about the "reasonably
                    well-behaved" part
        \_ one way to do stats is to always optimize the expected value of
           some cost function, and depending on what that cost function is,
           you pick the correct prbabilistic entity to be extremised (for
           example, likelihood or entropy, or some other function).  i think
           the sensible way to answer your question is "what is the cost
           you incur from using the wrong distribution" in terms of the cost

           function you're trying to maximize. i would say mutual information
           is a nice hint, but you really need to watch out for what you
           use the distribution for. -ali
           \_ see above; what i'm looking for to start with is the cost
              function, and it's painfully intractable, both mathematically
              and computationally
              \_ it seems to be that you're saying you can't even SAMPLE from
                 p(x) where p is the correct distrib? if you can sample from
                 the dist, you can do what i'm suggesting.
                 \_ Dude.  If you can sample independently from the
                    distribution, the distribution is your bitch.  You need
                    about twelve samples to approximate it to the degree that
                    is generally needed (source: McKay).
                 \_ The problem is that I'm looking for asymptotic behaviour,
                    and while I can sample at my test sizes at the rate
                    of 5-20 hours per sample, sampling at any decent size
                    can take years per sample
           \_ Aren't you in compilers ali?  Stop studying AI!
        \_ The Kolmogorov-Smirnov test might be useful as well -- used for
           testing if two data sets come from the same parent
           distribution, or whether a data set is consistent with a
           predicted distribution.
           \_ noted, thx

7/10           \_ dude, its RH. Crash and Burn by definition.
                \_ yeah, especially that redhat box I just upgraded from
                   2.0.36 that had been up for 320 days.  Man what a piece
                   of junk.  -tom
                   \_ Man, I don't remember soda being up that long .. ever.
                      \_ I dont know a machine that does as much as soda on
                         so little.
                         \_ This doesn't explain the crashes at all.  Is
                            FreeBSD stable or not stable?  Make up your mind.
                            \_ Soda is running stock fbsd?
                        \_ Well, that particular box is the web server and
                           e-mail server for the Physics department, and is
                           a PII/266.   It's not as heavily used as soda but
                           it's not trivial use either.  -tom
                           \_ A single web server for a department?  How much
                              more trivial can it get?  C'mon tom, join us out
                              here and try out some redundancy, millions of
                              hits per day, db servers, app servers, load
                              balancing across multiple colos in multiple
                              countries.  It's a whole other world.
                   \_ that's nothing! my NT machine hasn't crashed in
                   over 500 hours!  hmmm. .. wait a minute.. that sucks.
                      \_ My penis was up longer than that.
                         \_ You must be having paraphimosis.  I suggest
                            you go see a physician immediately.
                         \_ This can actually be life threatening.  The above
                            is right.  Go see a doctor.  I suggest emergency
                            room.  You might not survive until you get a
                            regular appointment.
                 \_ your machine is up because it runs linux, not because of
                    redhat. redhat IS a piece of shit insofar as what it's
                    done to linux
                    \_ yeah, keep bitching about the one implementation
                    of linux that non cs people have a chance of using...
                    bill gates is smiling right now, you stupid fuck.
                    \_ Uhm... using?  What about RH makes it "usable" for the
                       non-geeks?  The install?  The GUI?  fbsd has a better
                       installer and the GUI isn't RH specific.