what is scalar expectancy theory?
455787
http://ruccs.rutgers.edu/slc/articles/Scalar.pdf#search='scalar%20expectancy%20theory%20gibbon'
311981
Yes, if you expect the unexpected, then it(the unexpected) is expected.  Of course, if you are expecting the unexpected, then the expected becomes your unexpected.  No matter what you expect, there will always be someone that will ask, "Did you expect that?"  I expect you will eventually be surprised by how much you expect of others even in unexpected situations.  By the same token, if you expect more will you always be disappointed?  and if you expect less are you lowering your standards?  And just what are Great Expectations???
172645
Try this website, maybe it can answers some of your questions:\nhttp://en.wikipedia.org/wiki/Special:Search?search=interpretive+theory
803485
I think it's p=problem, i=infere' g=gather info? t=test e=expirement\n           good luck
879915
From Wikipedia, the free encyclopedia\nJump to: navigation, search\nProbability theory is the mathematical study of phenomena characterized by randomness or uncertainty.\n\nMore precisely, probability is used for modelling situations when the result of an experiment, realized under the same circumstances, produces different results (typically throwing a dice or a coin).\n\nMathematicians and actuaries think of probabilities as numbers in the closed interval from 0 to 1 assigned to "events" whose occurrence or failure to occur is random. Probabilities P(A) are assigned to events A according to the probability axioms.\n\nThe probability that an event A occurs given the known occurrence of an event B is the conditional probability of A given B; its numerical value is  (as long as P(B) is nonzero). If the conditional probability of A given B is the same as the ("unconditional") probability of A, then A and B are said to be independent events. That this relation between A and B is symmetric may be seen more readily by realizing that it is the same as saying  when A and B are independent events.\n\nTwo crucial concepts in the theory of probability are those of a random variable and of the probability distribution of a random variable; see those articles for more information.\n\nContents [hide]\n1 A somewhat more abstract view of probability \n2 Philosophy of application of probability \n3 See also \n4 Bibliography \n \n\n\n[edit] A somewhat more abstract view of probability\nMathematicians usually take probability theory to be the study of probability spaces and random variables — an approach introduced by Kolmogorov in the 1930s. A probability space is a triple , where\n\nΩ is a non-empty set, sometimes called the "sample space," each of whose members is thought of as a potential outcome of a random experiment. For example, if 100 voters are to be drawn randomly from among all voters in California and asked whom they will vote for governor, then the set of all sequences of 100 Californian voters would be the sample space Ω. \n is a σ-algebra of subsets of Ω - its members are called "events." For example the set of all sequences of 100 Californian voters in which at least 60 will vote for Schwarzenegger is identified with the "event" that at least 60 of the 100 chosen voters will so vote. To say that  is a σ-algebra implies per definition that it contains Ω, that the complement of any event is an event, and that the union of any (finite or countably infinite) sequence of events is an event. So for this example  contains: (1) the set of all sequences of 100 where at least 60 vote for Schwarzenegger; (2) the set of all sequences of 100 where fewer than 60 vote for Schwarzenegger (the converse of (1)); (3) the sample space Ω as above; and (4) the empty set. \nP is a probability measure on , i.e., a measure such that P(Ω) = 1. \nIt is important to note that P is a function defined on  and not on Ω, and often not on the complete powerset  either. Not every set of outcomes is an event.\n\nIf Ω is denumerable we almost always define  as the power set of Ω, i.e  which is trivially a σ-algebra and the biggest one we can create using Ω. In a discrete space we can therefore omit  and just write (Ω,P) to define it. If on the other hand Ω is non-denumerable and we use  we get into trouble defining our probability measure P because  is too 'huge', i.e. there will often be sets to which it will be impossible to assign a unique measure, giving rise to problems like the Banach–Tarski paradox. So we have to use a smaller σ-algebra  (e.g. the Borel algebra of Ω, which is the smallest σ-algebra that makes all open sets measurable).\n\nA random variable X is a measurable function on Ω. For example, the number of voters who will vote for Schwarzenegger in the aforementioned sample of 100 is a random variable.\n\nIf X is any random variable, the notation , is shorthand for ,
385428
Something expected; a possibility. \nprospects \nChances. \nFinancial expectations, especially of success. \n\nA potential customer, client, or purchaser. \nA candidate deemed likely to succeed. \nThe direction in which an object, such as a building, faces; an outlook. \nSomething presented to the eye; a scene: a pleasant prospect. \nThe act of surveying or examining. \n\nThe location or probable location of a mineral deposit. \nAn actual or probable mineral deposit. \nThe mineral yield obtained by working an ore
180512
salient - prominent \n\nmodern social and management research \n\n"positivism" and "idealism" are avenues toward (nurture) ie. behaviorism as a tool to control populations and idividuals. \n\nTo understand the basic starting point one looks at (nature) with evolutionary psych as a tool to understand basic drives.
15436
1. Jessica M Utts and Robert F Heckard (2006) Statistical Ideas and Methods, Thomson Brookes/Cole \n*** (3 stars)\n2. Gerald Keller and Brian Warrack, Statistics for Management and Economics –6th Edition, Duxbury. This textbook comes with a CD-ROM comprising applets for interactive examples, a student study guide and data files.\n****(4 stars) - quite good
131974
nice theory will it work? logic is there
757005
search for biefield-brown effect on the web.
942536
yes work is a scalar quanitity ....\n\nforce when applied on a body causes movement(displacement) and hence work is done on the body ...\n\nW=F.S( here we take dot product of vectors hence we get a scalar)\n\n\nhere mod(W)=mod(F)*mod(S)*cos(X) (Xis angle btwn force and displacement)\n  \n i.e w=0 when x is 90 degrees\n      w=f.s when x is 0 degrees\n     w= - f.s when x is 180 degrees\nhence depending on direction of force w.r.t displacement the work done varies...
111866
The theory delves into concepts of predestination, predetermination, and free-will. It proposes that human beings, animals, and others are really not in control of their own lives. Rather, what we do, when we do it, and how we go about doing it are determined by a complex set of interactions provided by the environment, people around us, etc. It is not hard to imagine some machine or random algorithm controlling these interactions, much like AI in a video game (FEAR, call of duty II...).
595965
Lamarckism is a term used for Lamarckian evolution, a theory put forward by the French biologist Jean-Baptiste Pierre Antoine de Monet, Chevalier de Lamarck, based on heritability of acquired characteristics, the once widely accepted idea that an organism can acquire characteristics during its lifetime and pass them on to its offspring, in contrast to the now commonly accepted Darwinian theory of Natural selection; the idea that individual organisms which possess genetic variations giving them advantageous heritable traits are more likely to survive and reproduce and, in doing so, to increase the frequency of such traits in subsequent generations.
326954
I did not take this specific course in college however I have studied it extensively since I have been practicing. I honestly believe it supplies more answers than many of the theorist were able to provide.  It of course is used in conjunction with theories in practice but there is honestly an area you miss out if you don't cover it.  Try reading Molecules of Emotion, I can't think of the author, she writes in a way that is very down to earth and yet really explores the impact of emotion on neurochemistry.  From their it is easier to expand into the concepts of behavior.
951978
Look up convergence theory on www.colorado.edu/communication/met.  It will explain this theory in fairly simple terms.
147570
Great Expectstions is a "great" book, but I understand yourneed for a study guide.  There's an excellent study guide at http://www.eriding.net/amoore/prose/greatexpectations.htm\n\nCheck it out.  I've included two others.  Good luck!
1003920
i am not sure with who came up with the concept, but this might be usefull \n\nhttp://en.wikipedia.org/wiki/Probability_Density_Function