Deductive Reasoning
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
There Is No Pure Empirical Reasoning
There Is No Pure Empirical Reasoning 1. Empiricism and the Question of Empirical Reasons Empiricism may be defined as the view there is no a priori justification for any synthetic claim. Critics object that empiricism cannot account for all the kinds of knowledge we seem to possess, such as moral knowledge, metaphysical knowledge, mathematical knowledge, and modal knowledge.1 In some cases, empiricists try to account for these types of knowledge; in other cases, they shrug off the objections, happily concluding, for example, that there is no moral knowledge, or that there is no metaphysical knowledge.2 But empiricism cannot shrug off just any type of knowledge; to be minimally plausible, empiricism must, for example, at least be able to account for paradigm instances of empirical knowledge, including especially scientific knowledge. Empirical knowledge can be divided into three categories: (a) knowledge by direct observation; (b) knowledge that is deductively inferred from observations; and (c) knowledge that is non-deductively inferred from observations, including knowledge arrived at by induction and inference to the best explanation. Category (c) includes all scientific knowledge. This category is of particular import to empiricists, many of whom take scientific knowledge as a sort of paradigm for knowledge in general; indeed, this forms a central source of motivation for empiricism.3 Thus, if there is any kind of knowledge that empiricists need to be able to account for, it is knowledge of type (c). I use the term “empirical reasoning” to refer to the reasoning involved in acquiring this type of knowledge – that is, to any instance of reasoning in which (i) the premises are justified directly by observation, (ii) the reasoning is non- deductive, and (iii) the reasoning provides adequate justification for the conclusion. -
A Philosophical Treatise on the Connection of Scientific Reasoning
mathematics Review A Philosophical Treatise on the Connection of Scientific Reasoning with Fuzzy Logic Evangelos Athanassopoulos 1 and Michael Gr. Voskoglou 2,* 1 Independent Researcher, Giannakopoulou 39, 27300 Gastouni, Greece; [email protected] 2 Department of Applied Mathematics, Graduate Technological Educational Institute of Western Greece, 22334 Patras, Greece * Correspondence: [email protected] Received: 4 May 2020; Accepted: 19 May 2020; Published:1 June 2020 Abstract: The present article studies the connection of scientific reasoning with fuzzy logic. Induction and deduction are the two main types of human reasoning. Although deduction is the basis of the scientific method, almost all the scientific progress (with pure mathematics being probably the unique exception) has its roots to inductive reasoning. Fuzzy logic gives to the disdainful by the classical/bivalent logic induction its proper place and importance as a fundamental component of the scientific reasoning. The error of induction is transferred to deductive reasoning through its premises. Consequently, although deduction is always a valid process, it is not an infallible method. Thus, there is a need of quantifying the degree of truth not only of the inductive, but also of the deductive arguments. In the former case, probability and statistics and of course fuzzy logic in cases of imprecision are the tools available for this purpose. In the latter case, the Bayesian probabilities play a dominant role. As many specialists argue nowadays, the whole science could be viewed as a Bayesian process. A timely example, concerning the validity of the viruses’ tests, is presented, illustrating the importance of the Bayesian processes for scientific reasoning. -
Arguments Vs. Explanations
Arguments vs. Explanations Arguments and explanations share a lot of common features. In fact, it can be hard to tell the difference between them if you look just at the structure. Sometimes, the exact same structure can function as an argument or as an explanation depending on the context. At the same time, arguments are very different in terms of what they try to accomplish. Explaining and arguing are very different activities even though they use the same types of structures. In a similar vein, building something and taking it apart are two very different activities, but we typically use the same tools for both. Arguments and explanations both have a single sentence as their primary focus. In an argument, we call that sentence the “conclusion”, it’s what’s being argued for. In an explanation, that sentence is called the “explanandum”, it’s what’s being explained. All of the other sentences in an argument or explanation are focused on the conclusion or explanandum. In an argument, these other sentences are called “premises” and they provide basic reasons for thinking that the conclusion is true. In an explanation, these other sentences are called the “explanans” and provide information about how or why the explanandum is true. So in both cases we have a bunch of sentences all focused on one single sentence. That’s why it’s easy to confuse arguments and explanations, they have a similar structure. Premises/Explanans Conclusion/Explanandum What is an argument? An argument is an attempt to provide support for a claim. One useful way of thinking about this is that an argument is, at least potentially, something that could be used to persuade someone about the truth of the argument’s conclusion. -
Notes on Pragmatism and Scientific Realism Author(S): Cleo H
Notes on Pragmatism and Scientific Realism Author(s): Cleo H. Cherryholmes Source: Educational Researcher, Vol. 21, No. 6, (Aug. - Sep., 1992), pp. 13-17 Published by: American Educational Research Association Stable URL: http://www.jstor.org/stable/1176502 Accessed: 02/05/2008 14:02 Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/action/showPublisher?publisherCode=aera. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit organization founded in 1995 to build trusted digital archives for scholarship. We enable the scholarly community to preserve their work and the materials they rely upon, and to build a common research platform that promotes the discovery and use of these resources. For more information about JSTOR, please contact [email protected]. http://www.jstor.org Notes on Pragmatismand Scientific Realism CLEOH. CHERRYHOLMES Ernest R. House's article "Realism in plicit declarationof pragmatism. Here is his 1905 statement ProfessorResearch" (1991) is informative for the overview it of it: of scientificrealism. -
Form and Explanation
Form and Explanation Jonathan Kramnick and Anahid Nersessian What does form explain? More often than not, when it comes to liter- ary criticism, form explains everything. Where form refers “to elements of a verbal composition,” including “rhythm, meter, structure, diction, imagery,” it distinguishes ordinary from figurative utterance and thereby defines the literary per se.1 Where form refers to the disposition of those elements such that the work of which they are a part mimes a “symbolic resolution to a concrete historical situation,” it distinguishes real from vir- tual phenomena and thereby defines the task of criticism as their ongoing adjudication.2 Both forensic and exculpatory in their promise, form’s ex- planations have been applied to circumstances widely disparate in scale, character, and significance. This is nothing new, but a recent flurry of de- bates identifying new varieties of form has thrown the unruliness of its application into relief. Taken together, they suggest that to give an account of form is to contribute to the work of making sense of linguistic meaning, aesthetic production, class struggle, objecthood, crises in the humanities and of the planet, how we read, why we read, and what’s wrong with these queries of how and why. In this context, form explains what we cannot: what’s the point of us at all? Contemporary partisans of form maintain that their high opinion of its exegetical power is at once something new in the field and the field’s 1. René Wellek, “Concepts of Form and Structure in Twentieth-Century Criticism,” Concepts of Criticism (New Haven, Conn., 1963), p. -
What Is a Philosophical Analysis?
JEFFREY C. KING WHAT IS A PHILOSOPHICAL ANALYSIS? (Received 24 January 1996) It is common for philosophers to offer philosophical accounts or analyses, as they are sometimes called, of knowledge, autonomy, representation, (moral) goodness, reference, and even modesty.1 These philosophical analyses raise deep questions. What is it that is being analyzed (i.e. what sorts of things are the objects of analysis)? What sort of thing is the analysis itself (a proposition? sentence?)? Under what conditions is an analysis correct? How can a correct analysis be informative? How, if at all, does the production of philo- sophical analyses differ from what scientists do? The purpose of the present paper is to provide answers to these questions. The traditional answers to the ®rst and last of these questions are that concepts are the objects of philosophical analysis and that philo- sophical analyses differ from the results of scienti®c investigation in being conceptual analyses. Like many philosophers I am suspicious of the notions of concept and conceptual analysis as traditionally understood. Though the critique of these notions is beyond the scope of the present work, the answers I shall give to the questions raised above shall not invoke concepts (understood as things distinct from properties).2 I count it as a virtue of my account that it is able to provide answers to the questions raised above without an appeal to concepts. And to the extent that it has been felt that concepts are needed to answer these questions, the present account weakens the case for positing concepts. Before addressing these questions, however, we shall make the simplifying assumption that analyses are given in a ªcanonical formº. -
Generics Analysis Canberra Plan.Pdf
Philosophical Perspectives, 26, Philosophy of Mind, 2012 CONCEPTS, ANALYSIS, GENERICS AND THE CANBERRA PLAN1 Mark Johnston Princeton University Sarah-Jane Leslie2 Princeton University My objection to meanings in the theory of meaning is not that they are abstract or that their identity conditions are obscure, but that they have no demonstrated use.3 —Donald Davidson “Truth and Meaning” From time to time it is said that defenders of conceptual analysis would do well to peruse the best empirically supported psychological theories of concepts, and then tailor their notions of conceptual analysis to those theories of what concepts are.4 As against this, there is an observation — traceable at least as far back to Gottlob Frege’s attack on psychologism in “The Thought” — that might well discourage philosophers from spending a week or two with the empirical psychological literature. The psychological literature is fundamentally concerned with mental representations, with the mental processes of using these in classification, characterization and inference, and with the sub-personal bases of these processes. The problem is that for many philosophers, concepts could not be mental items. (Jerry Fodor is a notable exception, we discuss him below.) We would like to set out this difference of focus in some detail and then propose a sort of translation manual, or at least a crucial translational hint, one which helps in moving between philosophical and psychological treatments of concepts. Then we will consider just how, given the translation, the relevant -
The Ontic Account of Scientific Explanation
Chapter 2 The Ontic Account of Scientific Explanation Carl F. Craver Abstract According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331– 496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. -
Analysis - Identify Assumptions, Reasons and Claims, and Examine How They Interact in the Formation of Arguments
Analysis - identify assumptions, reasons and claims, and examine how they interact in the formation of arguments. Individuals use analytics to gather information from charts, graphs, diagrams, spoken language and documents. People with strong analytical skills attend to patterns and to details. They identify the elements of a situation and determine how those parts interact. Strong interpretations skills can support high quality analysis by providing insights into the significance of what a person is saying or what something means. Inference - draw conclusions from reasons and evidence. Inference is used when someone offers thoughtful suggestions and hypothesis. Inference skills indicate the necessary or the very probable consequences of a given set of facts and conditions. Conclusions, hypotheses, recommendations or decisions that are based on faulty analysis, misinformation, bad data or biased evaluations can turn out to be mistaken, even if they have reached using excellent inference skills. Evaluative - assess the credibility of sources of information and the claims they make, and determine the strength and weakness or arguments. Applying evaluation skills can judge the quality of analysis, interpretations, explanations, inferences, options, opinions, beliefs, ideas, proposals, and decisions. Strong explanation skills can support high quality evaluation by providing evidence, reasons, methods, criteria, or assumptions behind the claims made and the conclusions reached. Deduction - decision making in precisely defined contexts where rules, operating conditions, core beliefs, values, policies, principles, procedures and terminology completely determine the outcome. Deductive reasoning moves with exacting precision from the assumed truth of a set of beliefs to a conclusion which cannot be false if those beliefs are untrue. Deductive validity is rigorously logical and clear-cut. -
Conceptual Analysis and Reductive Explanation
Conceptual Analysis and Reductive Explanation David J. Chalmers and Frank Jackson Philosophy Program Research School of Social Sciences Australian National University 1 Introduction Is conceptual analysis required for reductive explanation? If there is no a priori entailment from microphysical truths to phenomenal truths, does reductive explanation of the phenomenal fail? We say yes (Chalmers 1996; Jackson 1994, 1998). Ned Block and Robert Stalnaker say no (Block and Stalnaker 1999). A number of issues can be distinguished: (1) Is there an a priori entailment from microphysical truths to ordinary macroscopic truths? (2) If there is no a priori entailment from microphysical truths to phenomenal truths, does reductive explanation of the phenomenal fail? (3) If there is no a priori entailment from microphysical truths to phenomenal truths, is physicalism about the phenomenal false? (4) Is there an a priori entailment from microphysical truths to phenomenal truths? We hold that the first three questions should be answered positively (with some qualifications to be outlined). Block and Stalnaker hold that the first three questions should be answered negatively. Their central strategy is to argue for a negative answer to the first question, and to use this conclusion to argue for a negative answer to the second and third questions. They argue that truths about water and about life, for example, are not entailed a priori by microphysical truths, but that this is no bar to the reductive explanation and physical constitution of water and of life. In this paper, we will address Block and Stalnaker’s arguments for a negative answer to the first three questions, while remaining neutral on the fourth. -
An Introduction to Philosophy
An Introduction to Philosophy W. Russ Payne Bellevue College Copyright (cc by nc 4.0) 2015 W. Russ Payne Permission is granted to copy, distribute and/or modify this document with attribution under the terms of Creative Commons: Attribution Noncommercial 4.0 International or any later version of this license. A copy of the license is found at http://creativecommons.org/licenses/by-nc/4.0/ 1 Contents Introduction ………………………………………………. 3 Chapter 1: What Philosophy Is ………………………….. 5 Chapter 2: How to do Philosophy ………………….……. 11 Chapter 3: Ancient Philosophy ………………….………. 23 Chapter 4: Rationalism ………….………………….……. 38 Chapter 5: Empiricism …………………………………… 50 Chapter 6: Philosophy of Science ………………….…..… 58 Chapter 7: Philosophy of Mind …………………….……. 72 Chapter 8: Love and Happiness …………………….……. 79 Chapter 9: Meta Ethics …………………………………… 94 Chapter 10: Right Action ……………………...…………. 108 Chapter 11: Social Justice …………………………...…… 120 2 Introduction The goal of this text is to present philosophy to newcomers as a living discipline with historical roots. While a few early chapters are historically organized, my goal in the historical chapters is to trace a developmental progression of thought that introduces basic philosophical methods and frames issues that remain relevant today. Later chapters are topically organized. These include philosophy of science and philosophy of mind, areas where philosophy has shown dramatic recent progress. This text concludes with four chapters on ethics, broadly construed. I cover traditional theories of right action in the third of these. Students are first invited first to think about what is good for themselves and their relationships in a chapter of love and happiness. Next a few meta-ethical issues are considered; namely, whether they are moral truths and if so what makes them so. -
Relations Between Inductive Reasoning and Deductive Reasoning
Journal of Experimental Psychology: © 2010 American Psychological Association Learning, Memory, and Cognition 0278-7393/10/$12.00 DOI: 10.1037/a0018784 2010, Vol. 36, No. 3, 805–812 Relations Between Inductive Reasoning and Deductive Reasoning Evan Heit Caren M. Rotello University of California, Merced University of Massachusetts Amherst One of the most important open questions in reasoning research is how inductive reasoning and deductive reasoning are related. In an effort to address this question, we applied methods and concepts from memory research. We used 2 experiments to examine the effects of logical validity and premise– conclusion similarity on evaluation of arguments. Experiment 1 showed 2 dissociations: For a common set of arguments, deduction judgments were more affected by validity, and induction judgments were more affected by similarity. Moreover, Experiment 2 showed that fast deduction judgments were like induction judgments—in terms of being more influenced by similarity and less influenced by validity, compared with slow deduction judgments. These novel results pose challenges for a 1-process account of reasoning and are interpreted in terms of a 2-process account of reasoning, which was implemented as a multidimensional signal detection model and applied to receiver operating characteristic data. Keywords: reasoning, similarity, mathematical modeling An important open question in reasoning research concerns the arguments (Rips, 2001). This technique can highlight similarities relation between induction and deduction. Typically, individual or differences between induction and deduction that are not con- studies of reasoning have focused on only one task, rather than founded by the use of different materials (Heit, 2007). It also examining how the two are connected (Heit, 2007).