Lecture 2 Views of Karl Popper
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Truth, Rationality, and the Growth of Scientific Knowledge
....... CONJECTURES sense similar to that in which processes or things may be said to be parts of the world; that the world consists of facts in a sense in which it may be said to consist of (four dimensional) processes or of (three dimensional) things. They believe that, just as certain nouns are names of things, sentences are names of facts. And they sometimes even believe that sentences are some- thing like pictures of facts, or that they are projections of facts.7 But all this is mistaken. The fact that there is no elephant in this room is not one of the processes or parts ofthe world; nor is the fact that a hailstorm in Newfound- 10 land occurred exactIy I I I years after a tree collapsed in the New Zealand bush. Facts are something like a common product oflanguage and reality; they are reality pinned down by descriptive statements. They are like abstracts from TRUTH, RATIONALITY, AND THE a book, made in a language which is different from that of the original, and determined not only by the original book but nearly as much by the principles GROWTH OF SCIENTIFIC KNOWLEDGE of selection and by other methods of abstracting, and by the means of which the new language disposes. New linguistic means not only help us to describe 1. THE GROWTH OF KNOWLEDGE: THEORIES AND PROBLEMS new kinds of facts; in a way, they even create new kinds of facts. In a certain sense, these facts obviously existed before the new means were created which I were indispensable for their description; I say, 'obviously' because a calcula- tion, for example, ofthe movements of the planet Mercury of 100 years ago, MY aim in this lecture is to stress the significance of one particular aspect of carried out today with the help of the calculus of the theory of relativity, may science-its need to grow, or, if you like, its need to progress. -
Religious Language and Verificationism
© Michael Lacewing Religious language and verificationism AYER’S ARGUMENT In the 1930s, a school of philosophy arose called logical positivism, concerned with the foundations and possibility of knowledge. It developed a criterion for meaningful statements, called the principle of verification. On A J Ayer’s version (Language, Truth and Logic), the principle of verification states that a statement only has meaning if it is either analytic or empirically verifiable. (can be shown by experience to be probably true/false). ‘God exists’, and so all other talk of God, is such a statement, claims Ayer. Despite the best attempts of the ontological argument, we cannot prove ‘God exists’ from a priori premises using deduction alone. So ‘God exists’ is not analytically true. Therefore, to be meaningful, ‘God exists’ must be empirically verifiable. Ayer argues it is not. If a statement is an empirical hypothesis, it predicts our experience will be different depending on whether it is true or false. But ‘God exists’ makes no such predictions. So it is meaningless. Some philosophers argue that religious language attempts to capture something of religious experience, although it is ‘inexpressible’ in literal terms. Ayer responds that whatever religious experiences reveal, they cannot be said to reveal any facts. Facts are the content of statements that purport to be intelligible and can be expressed literally. If talk of God is non-empirical, it is literally unintelligible, hence meaningless. Responses We can object that many people do think that ‘God exists’ has empirical content. For example, the argument from design argues that the design of the universe is evidence for the existence of God. -
Greek and Latin Roots, Prefixes, and Suffixes
GREEK AND LATIN ROOTS, PREFIXES, AND SUFFIXES This is a resource pack that I put together for myself to teach roots, prefixes, and suffixes as part of a separate vocabulary class (short weekly sessions). It is a combination of helpful resources that I have found on the web as well as some tips of my own (such as the simple lesson plan). Lesson Plan Ideas ........................................................................................................... 3 Simple Lesson Plan for Word Study: ........................................................................... 3 Lesson Plan Idea 2 ...................................................................................................... 3 Background Information .................................................................................................. 5 Why Study Word Roots, Prefixes, and Suffixes? ......................................................... 6 Latin and Greek Word Elements .............................................................................. 6 Latin Roots, Prefixes, and Suffixes .......................................................................... 6 Root, Prefix, and Suffix Lists ........................................................................................... 8 List 1: MEGA root list ................................................................................................... 9 List 2: Roots, Prefixes, and Suffixes .......................................................................... 32 List 3: Prefix List ...................................................................................................... -
Principles of Scientific Inquiry
Chapter 2 PRINCIPLES OF SCIENTIFIC INQUIRY Introduction This chapter provides a summary of the principles of scientific inquiry. The purpose is to explain terminology, and introduce concepts, which are explained more completely in later chapters. Much of the content has been based on explanations and examples given by Wilson (1). The Scientific Method Although most of us have heard, at some time in our careers, that research must be carried out according to “the scientific method”, there is no single, scientific method. The term is usually used to mean a systematic approach to solving a problem in science. Three types of investigation, or method, can be recognized: · The Observational Method · The Experimental (and quasi-experimental) Methods, and · The Survey Method. The observational method is most common in the natural sciences, especially in fields such as biology, geology and environmental science. It involves recording observations according to a plan, which prescribes what information to collect, where it should be sought, and how it should be recorded. In the observational method, the researcher does not control any of the variables. In fact, it is important that the research be carried out in such a manner that the investigations do not change the behaviour of what is being observed. Errors introduced as a result of observing a phenomenon are known as systematic errors because they apply to all observations. Once a valid statistical sample (see Chapter Four) of observations has been recorded, the researcher analyzes and interprets the data, and develops a theory or hypothesis, which explains the observations. The experimental method begins with a hypothesis. -
Sacred Rhetorical Invention in the String Theory Movement
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Communication Studies Theses, Dissertations, and Student Research Communication Studies, Department of Spring 4-12-2011 Secular Salvation: Sacred Rhetorical Invention in the String Theory Movement Brent Yergensen University of Nebraska-Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/commstuddiss Part of the Speech and Rhetorical Studies Commons Yergensen, Brent, "Secular Salvation: Sacred Rhetorical Invention in the String Theory Movement" (2011). Communication Studies Theses, Dissertations, and Student Research. 6. https://digitalcommons.unl.edu/commstuddiss/6 This Article is brought to you for free and open access by the Communication Studies, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Communication Studies Theses, Dissertations, and Student Research by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. SECULAR SALVATION: SACRED RHETORICAL INVENTION IN THE STRING THEORY MOVEMENT by Brent Yergensen A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy Major: Communication Studies Under the Supervision of Dr. Ronald Lee Lincoln, Nebraska April, 2011 ii SECULAR SALVATION: SACRED RHETORICAL INVENTION IN THE STRING THEORY MOVEMENT Brent Yergensen, Ph.D. University of Nebraska, 2011 Advisor: Ronald Lee String theory is argued by its proponents to be the Theory of Everything. It achieves this status in physics because it provides unification for contradictory laws of physics, namely quantum mechanics and general relativity. While based on advanced theoretical mathematics, its public discourse is growing in prevalence and its rhetorical power is leading to a scientific revolution, even among the public. -
Hempel and Confirmation Theory
Hempel and Confirmation Theory Jan Sprenger* June 15, 2020 Carl Gustav Hempel (1905–1997) was one of the primary exponents of logical empiricism. As a student and member of the Gesellschaft für em- pirische Philosophie in Berlin, alongside Reichenbach and Grelling, he wit- nessed the emergence of logical empiricism as a philosophical program. From the mid-1930s onwards, his contributions shaped its development, too. Hempel studied primarily in Göttingen and Berlin, but in 1929/30, he also spent a semester in Vienna studying with Carnap and partici- pated in the activities of the Vienna Circle. Both societies joined forces for organizing scientific events, and founded the journal Erkenntnis in 1930, where many seminal papers of logical empiricism were published, with Carnap and Reichenbach as editors. While the work of the Berlin philosophers is congenial to the project of the Vienna Circle, there are important differences, too. Neither Hempel nor his mentor Reichenbach identified “scientific philosophy” with the project of cleansing science of meaningless statements (e.g., Carnap 1930). Rather, Hempel extensively used a method that Carnap would apply in later works on probability and confirmation (Carnap 1950, 1952): expli- cation, that is, the replacement of a vague and imprecise pre-theoretical concept (e.g., “confirmation”) by a fruitful and precise concept (e.g., a formal confirmation criterion). Relying on the method of explication, Hempel developed adequacy conditions on a qualitative concept of con- firmation (Hempel 1943, 1945a,b), a probabilistic measure of degree of *Contact information: Center for Logic, Language and Cognition (LLC), Department of Philosophy and Education Sciences, Università degli Studi di Torino, Via Sant’Ottavio 20, 10124 Torino, Italy. -
This Is Dr. Chumney. the Focus of This Lecture Is Hypothesis Testing –Both What It Is, How Hypothesis Tests Are Used, and How to Conduct Hypothesis Tests
TRANSCRIPT: This is Dr. Chumney. The focus of this lecture is hypothesis testing –both what it is, how hypothesis tests are used, and how to conduct hypothesis tests. 1 TRANSCRIPT: In this lecture, we will talk about both theoretical and applied concepts related to hypothesis testing. 2 TRANSCRIPT: Let’s being the lecture with a summary of the logic process that underlies hypothesis testing. 3 TRANSCRIPT: It is often impossible or otherwise not feasible to collect data on every individual within a population. Therefore, researchers rely on samples to help answer questions about populations. Hypothesis testing is a statistical procedure that allows researchers to use sample data to draw inferences about the population of interest. Hypothesis testing is one of the most commonly used inferential procedures. Hypothesis testing will combine many of the concepts we have already covered, including z‐scores, probability, and the distribution of sample means. To conduct a hypothesis test, we first state a hypothesis about a population, predict the characteristics of a sample of that population (that is, we predict that a sample will be representative of the population), obtain a sample, then collect data from that sample and analyze the data to see if it is consistent with our hypotheses. 4 TRANSCRIPT: The process of hypothesis testing begins by stating a hypothesis about the unknown population. Actually we state two opposing hypotheses. The first hypothesis we state –the most important one –is the null hypothesis. The null hypothesis states that the treatment has no effect. In general the null hypothesis states that there is no change, no difference, no effect, and otherwise no relationship between the independent and dependent variables. -
Understanding the Progress of Science
Understanding the Progress of Science C. D. McCoy 30 May 2018 The central problem of epistemology has always been and still is the problem of the growth of knowledge. And the growth of knowledge can be studied best by studying the growth of scientific knowledge. —(Popper, 2002b, xix) Merely fact-minded sciences make merely fact-minded people. —(Husserl, 1970, 6) The growth of human knowledge is realized most dramatically in the growth of scientific knowledge. What we have come to know through science about the workings of our human bodies and the workings of heavenly bodies, among much else, astounds, especially in comparison to our accumulating knowledge of the commonplace and everyday. Impressed by the evident epistemic progress made by science, many philosophers during the 20th century thought that studying how scientific knowledge increases is a crucial task of epistemological inquiry, and, indeed, the progress of science has been a topic of considerable interest. Yet, eventually, late in the century, attention waned and for the most part shifted to other tasks. Recently, however, a provocative article by Bird has re-ignited philosophical interest in the topic of scientific progress (Bird, 2007). Bird criticizes what he takes to have been the most prominent accounts advanced in the 20th century and presses for what he views as a venerable but lately overlooked one. He claims that realist philosophers of science have often presumed that truth is the goal of science and progress to be properly characterized by an accu- mulation of truth or truths, and notes that anti-realists have often rejected truth as a goal of science and characterized progress in terms of, among other things, “problem-solving effectiveness.”1 He criticizes the former for overlooking the relevance of justification to progress and the latter for giving up on truth. -
The Scientific Method: Hypothesis Testing and Experimental Design
Appendix I The Scientific Method The study of science is different from other disciplines in many ways. Perhaps the most important aspect of “hard” science is its adherence to the principle of the scientific method: the posing of questions and the use of rigorous methods to answer those questions. I. Our Friend, the Null Hypothesis As a science major, you are probably no stranger to curiosity. It is the beginning of all scientific discovery. As you walk through the campus arboretum, you might wonder, “Why are trees green?” As you observe your peers in social groups at the cafeteria, you might ask yourself, “What subtle kinds of body language are those people using to communicate?” As you read an article about a new drug which promises to be an effective treatment for male pattern baldness, you think, “But how do they know it will work?” Asking such questions is the first step towards hypothesis formation. A scientific investigator does not begin the study of a biological phenomenon in a vacuum. If an investigator observes something interesting, s/he first asks a question about it, and then uses inductive reasoning (from the specific to the general) to generate an hypothesis based upon a logical set of expectations. To test the hypothesis, the investigator systematically collects data, either with field observations or a series of carefully designed experiments. By analyzing the data, the investigator uses deductive reasoning (from the general to the specific) to state a second hypothesis (it may be the same as or different from the original) about the observations. -
The P–T Probability Framework for Semantic Communication, Falsification, Confirmation, and Bayesian Reasoning
philosophies Article The P–T Probability Framework for Semantic Communication, Falsification, Confirmation, and Bayesian Reasoning Chenguang Lu School of Computer Engineering and Applied Mathematics, Changsha University, Changsha 410003, China; [email protected] Received: 8 July 2020; Accepted: 16 September 2020; Published: 2 October 2020 Abstract: Many researchers want to unify probability and logic by defining logical probability or probabilistic logic reasonably. This paper tries to unify statistics and logic so that we can use both statistical probability and logical probability at the same time. For this purpose, this paper proposes the P–T probability framework, which is assembled with Shannon’s statistical probability framework for communication, Kolmogorov’s probability axioms for logical probability, and Zadeh’s membership functions used as truth functions. Two kinds of probabilities are connected by an extended Bayes’ theorem, with which we can convert a likelihood function and a truth function from one to another. Hence, we can train truth functions (in logic) by sampling distributions (in statistics). This probability framework was developed in the author’s long-term studies on semantic information, statistical learning, and color vision. This paper first proposes the P–T probability framework and explains different probabilities in it by its applications to semantic information theory. Then, this framework and the semantic information methods are applied to statistical learning, statistical mechanics, hypothesis evaluation (including falsification), confirmation, and Bayesian reasoning. Theoretical applications illustrate the reasonability and practicability of this framework. This framework is helpful for interpretable AI. To interpret neural networks, we need further study. Keywords: statistical probability; logical probability; semantic information; rate-distortion; Boltzmann distribution; falsification; verisimilitude; confirmation measure; Raven Paradox; Bayesian reasoning 1. -
Degrees of Riskiness, Falsifiability, and Truthlikeness. a Neo-Popperian
Degrees of riskiness, falsifiability, and truthlikeness. A neo-Popperian account applicable to probabilistic theories. Leander Vignero Sylvia Wenmackers [email protected] [email protected] KU Leuven, Institute of Philosophy, Centre for Logic and Philosophy of Science, Kardinaal Mercierplein 2 { bus 3200, 3000 Leuven, Belgium. July 7, 2021 (Forthcoming in Synthese.) Abstract In this paper, we take a fresh look at three Popperian concepts: riskiness, falsifiability, and truthlikeness (or verisimilitude) of scien- tific hypotheses or theories. First, we make explicit the dimensions that underlie the notion of riskiness. Secondly, we examine if and how degrees of falsifiability can be defined, and how they are related to var- ious dimensions of the concept of riskiness as well as the experimental context. Thirdly, we consider the relation of riskiness to (expected degrees of) truthlikeness. Throughout, we pay special attention to probabilistic theories and we offer a tentative, quantitative account of verisimilitude for probabilistic theories. \Modern logic, as I hope is now evident, has the effect of enlarging our abstract imagination, and providing an infinite number of possible hypotheses to be applied in the analysis of any complex fact." { Russell (1914, p. 58). A theory is falsifiable if it allows us to deduce predictions that can be compared to evidence, which according to our background knowledge could arXiv:2107.03772v1 [physics.hist-ph] 8 Jul 2021 show the prediction | and hence the theory | to be false. In his defense of falsifiability as a demarcation criterion, Popper has stressed the importance of bold, risky claims that can be tested, for they allow science to make progress. -
Reexamining the Problem of Demarcating Science and Pseudoscience by Evan Westre B.A., Vancouver Island University, 2010 a Thesis
Reexamining the Problem of Demarcating Science and Pseudoscience By Evan Westre B.A., Vancouver Island University, 2010 A Thesis Submitted in Partial Fulfillment of the Requirements For the Degree of MASTER OF ARTS ©Evan Westre, 2014 All Rights Reserved. This thesis may not be reproduced in whole or in part, by photocopy or other means, without the permission of the author. Supervisory Committee Reexamining the Problem of Demarcating Science and Pseudoscience By Evan Westre B.A., Vancouver Island University, 2010 Dr. Audrey Yap: Supervisor (Department of Philosophy) Dr. Jeffrey Foss: Departmental Member (Department of Philosophy) ii Abstract Supervisory Committee Dr. Audrey Yap: Supervisor (Department of Philosophy) Dr. Jeffrey Foss: Departmental Member (Department of Philosophy) The demarcation problem aims to articulate the boundary between science and pseudoscience. Solutions to the problem have been notably raised by the logical positivists (verificationism), Karl Popper (falsificationism), and Imre Lakatos (methodology of research programmes). Due, largely, to the conclusions drawn by Larry Laudan, in a pivotal 1981 paper which dismissed the problem of demarcation as a “pseudo-problem”, the issue was brushed aside for years. Recently, however, there has been a revival of attempts to reexamine the demarcation problem and synthesize new solutions. My aim is to survey two of the contemporary attempts and to assess these approaches over and against the broader historical trajectory of the demarcation problem. These are the efforts of Nicholas Maxwell (aim-oriented empiricism), and Paul Hoyningen-Huene (systematicity). I suggest that the main virtue of the new attempts is that they promote a self-reflexive character within the sciences.