Mar 14

Climate Changes
During the late VERY LATE MATE ....Pleistocene, the retreat of the Wisconsin ice sheet caused
global climate changes and changes in local AND GLOBAL ENVIRONMENTS .

Temperatures became less homogenous, as winters became colder and summers became

Essentially, seasonality increased.
In addition, rainfall became more variable depending on the season, IN MARCH 2014 TEMPERATURES

ARE HIGHER THAN AVERAGE with distinctions between wet and dry seasons THEY ARE DRY ...BUT WHO KNOW'S


.During the deglaciation,many streams in the glacial floodplains experienced net degradation
and incision of their channels, and the water tables lowered, causing low order
streams to become sporadic and transient and springs to dry up or significantly reducedischarge 
As a result of this climatic shift, several changes occurred.

Some primary habitats were eliminated, while others
that may have been only marginal during THE GREAT PIB INCREASE OR GDP INCREASE ARE FINE



Wednesday, March 19, 2014 .....Which is better, data or theory?

One of the most annoying arguments that I see popping up again and again is the question of "Which is better, theory or data?" (A related bore-fest is "Which is better, induction or deduction?") Actually, you can't have one without the other. In a recent blog post, Paul Krugman points out that you can't have data without theory:
But you can’t be an effective fox just by letting the data speak for itself — because it never does. You use data to inform your analysis, you let it tell you that your pet hypothesis is wrong, but data are never a substitute for hard thinking. If you think the data are speaking for themselves, what you’re really doing is implicit theorizing, which is a really bad idea (because you can’t test your assumptions if you don’t even know what you’re assuming.)
True. Suppose you find a correlation between having an unfulfilling sex life and liking Charlie Kaufman movies. Does that mean that people watch Charlie Kaufman movies to ease the pain of their lame sex lives? Or did the fact that they watch Charlie Kaufman movies actually ruin their sex lives? Or are both the result of some third factor, such as being an insufferable hipster? If you don't pick one, you'll never be able to understand what's really going on. Even if all you care about is predictive power - you want to be able to catch someone watching a Charlie Kaufman movie and say "I bet girls won't touch that guy with a 10 foot pole" - you still need to assume that the correlation is stable over time, and your assumption is a theory. 
It's equally true that you can't actually have theory without data. A theory is always about something that you think is going on in the world, so you can't have something to theorize about without first seeing something happen in the world (i.e. data). For example, suppose my theory - which I deduced from some sort of a priori assumptions - is that watching Charlie Kaufman movies ruins one's sex life. I couldn't have made that theory without observing the existence of Charlie Kaufman movies.
So just as "data with no theory" is really just an implicit vague theory, "theory with no data" is really just sparse, unsystematic data. You can't have one without the other. 
But what you can do is be lazy with theory or be lazy with data. You can be an armchair philosopher, dreaming up ideas about how the world works without ever bothering to find out if your ideas are right. Then you get something like this:
Or you can be a "regression monkey", sitting there sifting for correlations without having any idea what you're looking at. Then you get something like this:
Obviously, if you're going to get good results, you shouldn't do either of these.
But which is a bigger menace to society, laziness about data or laziness about theory? Theory-laziness is seductive because it's easy - mining for correlations isn't very mentally taxing. But data-laziness is seductive because it's hard - the more complicated and intricate a theory you make, the smarter it makes you feel, even if the theory sucks.
In the past, data-laziness was probably more of a threat to humanity. Since systematic data was scarce, people had a tendency to sit around and daydream about how stuff might work. But now that Big Data is getting bigger and computing power is cheap, theory-laziness seems to be becoming more of a menace. The lure of Big Data is that we can get all our ideas from mining for patterns, but A) we get a lot of false patterns that way, and B) the patterns insidiously and subtly suggest interpretations for themselves, and those interpretations are often wrong.
So anyway, I hope this post destroys all of those "data vs. theory" arguments forever and ever. 
  1. Absolutely wonderful post--should be required reading for all undergrads.

    In the arts and humanities, data laziness is still very common, because any attempt to quantify these outputs is considered gauche, insensitive, or ham-fisted (adjectives often found in the first few paragraphs of lit theory papers).

    1. data is better....data is a android ergo is better than,,,,repeat the question please...
      Spiner reprised his role of Data in the Star Trek: Enterprise series finale ... from B4 into a new body which contained the memory engrams of Data's creator

      mountain's less pressure of o2 

      no the pattern's don't exist 

      this is a chaotic universe

      data big or small is observator dependent

      observation of data is dependent of quantum physics


      associal or social ones too...

      Information and correlation[edit]
      It is generally well established that any quantum mechanical measurement can be reduced to a set of yes/no questions or bits that are either 1 or 0.[citation needed] RQM makes use of this fact to formulate the state of a quantum system (relative to a given observer!) in terms of the physical notion of information developed by Claude Shannon. Any yes/no question can be described as a single bit of information. This should not be confused with the idea of a qubit from quantum information theory, because a qubit can be in a superposition of values, whilst the "questions" of RQM are ordinary binary variables.
      Any quantum measurement is fundamentally a physical interaction between the system being measured and some form of measuring apparatus. By extension, any physical interaction may be seen to be a form of quantum measurement, as all systems are seen as quantum systems in RQM. A physical interaction is seen as establishing a correlation between the system and the observer, and this correlation is what is described and predicted by the quantum formalism.
      But, Rovelli points out, this form of correlation is precisely the same as the definition of information in Shannon's theory. Specifically, an observer O observing a system S will, after measurement, have some degrees of freedom correlated with those of S. The amount of this correlation is given by log2k bits, where k is the number of possible values which this correlation may take — the number of "options" there are.
      All systems are quantum systems[edit]
      All physical interactions are, at bottom, quantum interactions, and must ultimately be governed by the same rules. Thus, an interaction between two particles does not, in RQM, differ fundamentally from an interaction between a particle and some "apparatus". There is no true wave collapse, in the sense in which it occurs in the Copenhagen interpretation.
      Because "state" is expressed in RQM as the correlation between two systems, there can be no meaning to "self-measurement". If observer O measures system S, S's "state" is represented as a correlation between O and S. O itself cannot say anything with respect to its own "state", because its own "state" is defined only relative to another observer, O'. If the S+O compound system does not interact with any other systems, then it will possess a clearly defined state relative to O'. However, because O's measurement of S breaks its unitary evolution with respect to O, O will not be able to give a full description of the S+O system (since it can only speak of the correlation between S and itself, not its own behaviour). A complete description of the (S+O)+O' system can only be given by a further, external observer, and so forth.
      Taking the model system discussed above, if O' has full information on the S+O system, it will know the Hamiltonians of both S and O, including the interaction Hamiltonian. Thus, the system will evolve entirely unitarily (without any form of collapse) relative to O', if O measures S. The only reason that O will perceive a "collapse" is because O has incomplete information on the system (specifically, O does not know its own Hamiltonian, and the interaction Hamiltonian for the measurement).

publicado por tstopps às 18:47
sinto-me: FINO WE ARE FINE

Março 2014








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