42 found
Sort by:
Disambiguations:
Malcolm Forster [23]Malcolm R. Forster [19]
See also:
Profile: Malcolm Forster (University of Wisconsin, Madison)
  1. Malcolm Forster, Chapter 1: An Introduction to Philosophy of Science.
    Deductive logic is about the validity of arguments. An argument is valid when its conclusion follows deductively from its premises. Here’s an example: If Alice is guilty then Bob is guilty, and Alice is guilty. Therefore, Bob is guilty. The validity of the argument has nothing to do with what the argument is about. It has nothing to do with the meaning, or content, of the argument beyond the meaning of logical phrases such as if…then. Thus, any argument of the (...)
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  2. Malcolm Forster, Chapter 3: Simplicity and Unification in Model Selection.
    This chapter examines four solutions to the problem of many models, and finds some fault or limitation with all of them except the last. The first is the naïve empiricist view that best model is the one that best fits the data. The second is based on Popper’s falsificationism. The third approach is to compare models on the basis of some kind of trade off between fit and simplicity. The fourth is the most powerful: Cross validation testing.
    Direct download  
     
    My bibliography  
     
    Export citation  
  3. Malcolm Forster, Chapter 2: Theories, Models, and Curves.
    The distinction itself is best explained as follows. At the empirical level (at the bottom), there are curves, or functions, or laws, such as PV = constant the Boyle’s example, or a = M/r 2 in Newton’s example. The first point is that such formulae are actually ambiguous as to the hypotheses they represent. They can be understood in two ways. In order to make this point clear, let me first introduce a terminological distinction between variables and parameters. Acceleration and (...)
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  4. Malcolm Forster, Discussion: Unification and Predictive Accuracy.
    Wayne Myrvold (2003) has captured an important feature of unified theories, and he has done so in Bayesian terms. What is not clear is whether the virtue of such unification is most clearly understood in terms of Bayesian confirmation. I argue that the virtue of such unification is better understood in terms of other truth-related virtues such as predictive accuracy.
    Direct download  
     
    My bibliography  
     
    Export citation  
  5. Malcolm Forster, Many Kinds of Confirmation.
    Type 1: This process occurs for half of the population. For this segment of the population, there is 10% chance of developing the disease. There is a test for the disease such that 90% of the people who have the disease in this case will test positive (event E), while the false positive rate is 10%, which means that there is a 10% chance of testing positive for the disease when they do not have the disease.
    Direct download  
     
    My bibliography  
     
    Export citation  
  6. Malcolm Forster, Percolation: An Easy Example of Renormalization.
    Kenneth Wilson won the Nobel Prize in Physics in 1982 for applying renormalization group, which he learnt from quantum field theory (QFT), to problems in statistical physics—the induced magnetization of materials (ferromagnetism) and the evaporation and condensation of fluids (phase transitions). See Wilson (1983). The renormalization group got its name from its early applications in QFT. There, it appeared to be a rather ad hoc method of subtracting away unwanted infinities. The further allegation was that the procedure is so horrendously (...)
    Direct download  
     
    My bibliography  
     
    Export citation  
  7. Malcolm Forster, Philosophy of the Quantitative Sciences.
    Deductive logic is about the property of arguments called validity. An argument has this property when its conclusion follows deductively from its premises. Here’s an example: If Alice is guilty then Bob is guilty, and Alice is guilty. Therefore, Bob is guilty. The important point is that the validity of this argument has nothing to do with the content of the argument. Any argument of the following form (called modus ponens) is valid: If P then Q, and P, therefore Q. (...)
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  8. Malcolm Forster, The Asymmetry Between Backwards and Forwards Regression.
    Suppose that the true structural equation is Y = X + U, where U is n(0,1), X is n(0,1), and X and U µ be the mean of X, y µ the mean of Y, x σ the standard deviation of are independent. Now let x..
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  9. Malcolm Forster, The Evolution of Inference.
    A and B in signaling games (Lewis 1969). Members of the population, such as our prehistoric pair, are occasionally faced with the following ‘game’. Let one of the players be the receiver and the other the sender. The receiver needs to know whether B is true or not, but only possesses information about whether A is true or not. In some environmental contexts, A is sufficient for B, in others it is not. The sender knows nothing about A or B, (...)
    Direct download  
     
    My bibliography  
     
    Export citation  
  10. Malcolm Forster, The Einsteinian Prediction of the Precession of Mercury's Perihelion.
    Puzzle solving in normal science involves a process of accommodation—auxiliary assumptions are changed, and parameter values are adjusted so as to eliminate the known discrepancies with the data. Accommodation is often contrasted with prediction. Predictions happen when one achieves a good fit with novel data without accommodation. So, what exactly is the distinction, and why is it important? The distinction, as I understand it, is relative to a model M and a data set D, where M is a set of (...)
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  11. Malcolm Forster, The Whewell-Mill Debate in a Nutshell.
    What is induction? John Stuart Mill (1874, p. 208) defined induction as the operation of discovering and proving general propositions. William Whewell (in Butts, 1989, p. 266) agrees with Mill’s definition as far as it goes. Is Whewell therefore assenting to the standard concept of induction, which talks of inferring a generalization of the form “All As are Bs” from the premise that “All observed As are Bs”? Does Whewell agree, to use Mill’s example, that inferring “All humans are mortal” (...)
    Direct download  
     
    My bibliography  
     
    Export citation  
  12. Malcolm Forster, Unification and Evidence.
    The Value of Good Illustrative Examples: In order to speak as generally as possible about science, philosophers of science have traditionally formulated their theses in terms of elementary logic and elementary probability theory. They often point to real scientific examples without explaining them in detail and/or use artificial examples that fail to fit with intricacies of real examples. Sometimes their illustrative examples are chosen to fit their framework, rather than the science. Frequently these are non-scientific examples, which distances the discussion (...)
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  13. Malcolm Forster, William Whewell (1794-1866).
    Whewell, William (b Lancaster, England, 24 May 1794; d Cambridge, England, 6 March 1866) Born the eldest son of a carpenter, William Whewell rose to become Master of Trinity College, Cambridge and a central figure in Victorian science. After attending the grammar school at Heversham in Westmorland, Whewell entered Trinity College, Cambridge and graduated Second Wrangler. He became a Fellow of the College in 1817, took his M.A. degree in 1819, and his D.D. degree in 1844.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  14. Prasanta S. Bandyopadhyay & Malcolm Forster (eds.) (forthcoming). Handbook of the Philosophy of Statistics. Elsevier.
    Translate to English
    |
     
    My bibliography  
     
    Export citation  
  15. Prasanta S. Bandyopadhyay & Malcolm Forster (eds.) (forthcoming). Philosophy of Statistics, Handbook of the Philosophy of Science, Volume 7. Elsevier.
  16. Malcolm R. Forster, I. A. Kieseppä, Dan Hausman, Alexei Krioukov, Stephen Leeds, Alan Macdonald & Larry Shapiro (forthcoming). The Conceptual Role of 'Temperature'in Statistical Mechanics: Or How Probabilistic Averages Maximize Predictive Accuracy. Philosophy of Science.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  17. Malcolm R. Forster (2011). Scientific Evidence. In Steven French & Juha Saatsi (eds.), Continuum Companion to the Philosophy of Science. Continuum. 179.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  18. Malcolm R. Forster (2010). Miraculous Consilience of Quantum Mechanics. In. In Ellery Eells & James Fetzer (eds.), The Place of Probability in Science. Springer. 201--228.
  19. Cristina Bicchieri, Jason McKenzie Alexander, Kevin T. Kelly, Kevin Js Zollman, Malcolm R. Forster, Predrag Šustar, Patrick Forber, Kenneth Reisman, Jay Odenbaugh & Yoichi Ishida (2007). 10. Philosophy of Chemistry. Philosophy of Science 74 (5).
     
    My bibliography  
     
    Export citation  
  20. Malcolm Forster (2007). A Philosopher's Guide to Empirical Success. Philosophy of Science 74 (5):588-600.
    The simple question, what is empirical success? turns out to have a surprisingly complicated answer. We need to distinguish between meritorious fit and ‘fudged fit', which is akin to the distinction between prediction and accommodation. The final proposal is that empirical success emerges in a theory dependent way from the agreement of independent measurements of theoretically postulated quantities. Implications for realism and Bayesianism are discussed. ‡This paper was written when I was a visiting fellow at the Center for Philosophy of (...)
    Direct download (7 more)  
     
    My bibliography  
     
    Export citation  
  21. Malcolm Forster (2006). Ellery Eells, 1953-2006. Proceedings and Addresses of the American Philosophical Association 80 (2):108 - 109.
    No categories
    Translate to English
    | Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  22. Malcolm R. Forster (2006). Counterexamples to a Likelihood Theory of Evidence. Minds and Machines 16 (3):319-338.
    The likelihood theory of evidence (LTE) says, roughly, that all the information relevant to the bearing of data on hypotheses (or models) is contained in the likelihoods. There exist counterexamples in which one can tell which of two hypotheses is true from the full data, but not from the likelihoods alone. These examples suggest that some forms of scientific reasoning, such as the consilience of inductions (Whewell, 1858. In Novum organon renovatum (Part II of the 3rd ed.). The philosophy of (...)
    Direct download (8 more)  
     
    My bibliography  
     
    Export citation  
  23. Malcolm Forster (2004). The Debate Between Whewell and Mill on the Nature of Scientific Induction. In Dov M. Gabbay, John Woods & Akihiro Kanamori (eds.), Handbook of the History of Logic. Elsevier. 10--93.
    No categories
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  24. Malcolm R. Forster & Alexey Kryukov (2003). The Emergence of the Macroworld: A Study of Intertheory Relations in Classical and Quantum Mechanics. Philosophy of Science 70 (5):1039-1051.
    Classical mechanics is empirically successful because the probabilistic mean values of quantum mechanical observables follow the classical equations of motion to a good approximation (Messiah 1970, 215). We examine this claim for the one‐dimensional motion of a particle in a box, and extend the idea by deriving a special case of the ideal gas law in terms of the mean value of a generalized force used to define “pressure.” The examples illustrate the importance of probabilistic averaging as a method of (...)
    Direct download (6 more)  
     
    My bibliography  
     
    Export citation  
  25. Malcolm R. Forster (2002). Predictive Accuracy as an Achievable Goal of Science. Proceedings of the Philosophy of Science Association 2002 (3):S124-S134.
    No categories
    Direct download (5 more)  
     
    My bibliography  
     
    Export citation  
  26. S. L. Zabell, Brian Skyrms, Elliott Sober, Malcolm R. Forster, Wayne C. Myrvold, William L. Harper, Rob Clifton, Itamar Pitowsky, Robyn M. Dawes & David Faust (2002). 10. It All Adds Up: The Dynamic Coherence of Radical Probabilism It All Adds Up: The Dynamic Coherence of Radical Probabilism (Pp. S98-S103). [REVIEW] Philosophy of Science 69 (S3).
    No categories
     
    My bibliography  
     
    Export citation  
  27. Malcolm R. Forster (1999). How Do Simple Rules `Fit to Reality' in a Complex World? Minds and Machines 9 (4):543-564.
    The theory of fast and frugal heuristics, developed in a new book called Simple Heuristics that make Us Smart (Gigerenzer, Todd, and the ABC Research Group, in press), includes two requirements for rational decision making. One is that decision rules are bounded in their rationality –- that rules are frugal in what they take into account, and therefore fast in their operation. The second is that the rules are ecologically adapted to the environment, which means that they `fit to reality.' (...)
    Direct download (7 more)  
     
    My bibliography  
     
    Export citation  
  28. Malcolm R. Forster (1995). Bayes and Bust: Simplicity as a Problem for a Probabilist's Approach to Confirmation. [REVIEW] British Journal for the Philosophy of Science 46 (3):399-424.
    The central problem with Bayesian philosophy of science is that it cannot take account of the relevance of simplicity and unification to confirmation, induction, and scientific inference. The standard Bayesian folklore about factoring simplicity into the priors, and convergence theorems as a way of grounding their objectivity are some of the myths that Earman's book does not address adequately. 1Review of John Earman: Bayes or Bust?, Cambridge, MA. MIT Press, 1992, £33.75cloth.
    Direct download (7 more)  
     
    My bibliography  
     
    Export citation  
  29. Malcolm R. Forster (1995). The Golfer's Dilemma: A Reply to Kukla on Curve-Fitting. British Journal for the Philosophy of Science 46 (3):348-360.
    Curve-fitting typically works by trading off goodness-of-fit with simplicity, where simplicity is measured by the number of adjustable parameters. However, such methods cannot be applied in an unrestricted way. I discuss one such correction, and explain why the exception arises. The same kind of probabilistic explanation offers a surprising resolution to a common-sense dilemma.
    Direct download (8 more)  
     
    My bibliography  
     
    Export citation  
  30. Malcolm R. Forster (1994). Non-Bayesian Foundations for Statistical Estimation, Prediction, and the Ravens Example. Erkenntnis 40 (3):357 - 376.
    The paper provides a formal proof that efficient estimates of parameters, which vary as as little as possible when measurements are repeated, may be expected to provide more accurate predictions. The definition of predictive accuracy is motivated by the work of Akaike (1973). Surprisingly, the same explanation provides a novel solution for a well known problem for standard theories of scientific confirmation — the Ravens Paradox. This is significant in light of the fact that standard Bayesian analyses of the paradox (...)
    Direct download (5 more)  
     
    My bibliography  
     
    Export citation  
  31. Malcolm Forster & Eric Saidel (1994). Connectionism and the Fate of Folk Psychology: A Reply to Ramsey, Stich and Garon. Philosophical Psychology 7 (4):437 – 452.
    Ramsey, Stick and Garon (1991) argue that if the correct theory of mind is some parallel distributed processing theory, then folk psychology must be false. Their idea is that if the nodes and connections that encode one representation are causally active then all representations encoded by the same set of nodes and connections are also causally active. We present a clear, and concrete, counterexample to RSG's argument. In conclusion, we suggest that folk psychology and connectionism are best understood as complementary (...)
    Direct download (4 more)  
     
    My bibliography  
     
    Export citation  
  32. Malcolm Forster & Elliott Sober (1994). How to Tell When Simpler, More Unified, or Less Ad Hoc Theories Will Provide More Accurate Predictions. British Journal for the Philosophy of Science 45 (1):1-35.
    Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike [1973], which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light (...)
    Direct download (10 more)  
     
    My bibliography  
     
    Export citation  
  33. Malcolm Forster (1991). Preconditions of Predication: From Qualia to Quantum Mechanics. Topoi 10 (1):13-26.
    Although in every inductive inference, an act of invention is requisite, the act soon slips out of notice. Although we bind together facts by superinducing upon them a new Conception, this Conception, once introduced and applied, is looked upon as inseparably connected with the facts, and necessarily implied in them. Having once had the phenomena bound together in their minds in virtue of the Conception men can no longer easily restore them back to the detached and incoherent condition in which (...)
    Direct download (6 more)  
     
    My bibliography  
     
    Export citation  
  34. Malcolm R. Forster (1990). Book Review:Scientific Discovery: Computational Explorations of the Creative Process Pat Langley, Herbert A. Simon, Gary L. Bradshaw, Jan M. Zytkow. [REVIEW] Philosophy of Science 57 (2):336-.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  35. Malcolm Forster (1988). Unification, Explanation, and the Composition of Causes in Newtonian Mechanics. Studies in History and Philosophy of Science 19 (1):55-101.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  36. Malcolm R. Forster (1988). Sober's Principle of Common Cause and the Problem of Comparing Incomplete Hypotheses. Philosophy of Science 55 (4):538-559.
    Sober (1984) has considered the problem of determining the evidential support, in terms of likelihood, for a hypothesis that is incomplete in the sense of not providing a unique probability function over the event space in its domain. Causal hypotheses are typically like this because they do not specify the probability of their initial conditions. Sober's (1984) solution to this problem does not work, as will be shown by examining his own biological examples of common cause explanation. The proposed solution (...)
    Direct download (6 more)  
     
    My bibliography  
     
    Export citation  
  37. Malcolm R. Forster (1988). The Confirmation of Common Component Causes. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:3 - 9.
    This paper aims to show how Whewell's notions of consilience and unification-explicated in more modern probabilistic terms provide a satisfying treatment of cases of scientific discovery Which require the postulatioin component causes to explain complex events. The results of this analysis support the received view that the increased unification and generality of theories leads to greater testability, and confirmation if the observations are favorable. This solves a puzzle raised by Cartwright in How the Laws of Physics Lie about the nature (...)
    No categories
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  38. Malcolm R. Forster (1986). Counterfactual Reasoning in the Bell-Epr Paradox. Philosophy of Science 53 (1):133-144.
    Skyrms's formulation of the argument against stochastic hidden variables in quantum mechanics using conditionals with chance consequences suffers from an ambiguity in its "conservation" assumption. The strong version, which Skyrms needs, packs in a "no-rapport" assumption in addition to the weaker statement of the "experimental facts." On the positive side, I argue that Skyrms's proof has two unnoted virtues (not shared by previous proofs): (1) it shows that certain difficulties that arise for deterministic hidden variable theories that exploit a nonclassical (...)
    Direct download (5 more)  
     
    My bibliography  
     
    Export citation  
  39. Malcolm R. Forster (1986). Unification and Scientific Realism Revisited. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:394 - 405.
    Van Fraassen has argued that quantum mechanics does not conform to the pattern of common cause explanation used by Salmon as a precise formulation of Smart's 'cosmic coincidence' argument for scientific realism. This paper adds to this list some common examples from classical physics that also do not conform to Salmon's explanatory schema. This is bad news and good news for the realist. The bad news is that Salmon's argument for realism does not work; the good news is that realism (...)
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  40. Malcolm R. Forster (1985). Book Review:How the Laws of Physics Lie Nancy Cartwright. [REVIEW] Philosophy of Science 52 (3):478-.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  41. Malcolm Forster, Discussion: Unification and Predictive Accuracy.
    Wayne Myrvold (2003) has captured an important feature of unified theories, and he has done so in Bayesian terms. What is not clear is whether the virtue of such unification is most clearly understood in terms of Bayesian confirmation. I argue that the virtue of such unification is better understood in terms of other truth-related virtues such as predictive accuracy.
    Translate to English
    | Direct download  
     
    My bibliography  
     
    Export citation  
  42. Malcolm R. Forster & Alexei Krioukov, How to ‘See Through’ the Ideal Gas Law in Terms of the Concepts of Quantum Mechanics.
    Textbooks in quantum mechanics frequently claim that quantum mechanics explains the success of classical mechanics because “the mean values [of quantum mechanical observables] follow the classical equations of motion to a good approximation,” while “the dimensions of the wave packet be small with respect to the characteristic dimensions of the problem.” The equations in question are Ehrenfest’s famous equations. We examine this case for the one-dimensional motion of a particle in a box, and extend the idea deriving a special case (...)
    Direct download  
     
    My bibliography  
     
    Export citation