Suggestion, Belief in the Paranormal, Proneness to Reality Testing Deficits and Perception of an Allegedly Haunted Building
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Generalized Linear Models (Glms)
San Jos´eState University Math 261A: Regression Theory & Methods Generalized Linear Models (GLMs) Dr. Guangliang Chen This lecture is based on the following textbook sections: • Chapter 13: 13.1 – 13.3 Outline of this presentation: • What is a GLM? • Logistic regression • Poisson regression Generalized Linear Models (GLMs) What is a GLM? In ordinary linear regression, we assume that the response is a linear function of the regressors plus Gaussian noise: 0 2 y = β0 + β1x1 + ··· + βkxk + ∼ N(x β, σ ) | {z } |{z} linear form x0β N(0,σ2) noise The model can be reformulate in terms of • distribution of the response: y | x ∼ N(µ, σ2), and • dependence of the mean on the predictors: µ = E(y | x) = x0β Dr. Guangliang Chen | Mathematics & Statistics, San Jos´e State University3/24 Generalized Linear Models (GLMs) beta=(1,2) 5 4 3 β0 + β1x b y 2 y 1 0 −1 0.0 0.2 0.4 0.6 0.8 1.0 x x Dr. Guangliang Chen | Mathematics & Statistics, San Jos´e State University4/24 Generalized Linear Models (GLMs) Generalized linear models (GLM) extend linear regression by allowing the response variable to have • a general distribution (with mean µ = E(y | x)) and • a mean that depends on the predictors through a link function g: That is, g(µ) = β0x or equivalently, µ = g−1(β0x) Dr. Guangliang Chen | Mathematics & Statistics, San Jos´e State University5/24 Generalized Linear Models (GLMs) In GLM, the response is typically assumed to have a distribution in the exponential family, which is a large class of probability distributions that have pdfs of the form f(x | θ) = a(x)b(θ) exp(c(θ) · T (x)), including • Normal - ordinary linear regression • Bernoulli - Logistic regression, modeling binary data • Binomial - Multinomial logistic regression, modeling general cate- gorical data • Poisson - Poisson regression, modeling count data • Exponential, Gamma - survival analysis Dr. -
How Prediction Statistics Can Help Us Cope When We Are Shaken, Scared and Irrational
EGU21-15219 https://doi.org/10.5194/egusphere-egu21-15219 EGU General Assembly 2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. How prediction statistics can help us cope when we are shaken, scared and irrational Yavor Kamer1, Shyam Nandan2, Stefan Hiemer1, Guy Ouillon3, and Didier Sornette4,5 1RichterX.com, Zürich, Switzerland 2Windeggstrasse 5, 8953 Dietikon, Zurich, Switzerland 3Lithophyse, Nice, France 4Department of Management,Technology and Economics, ETH Zürich, Zürich, Switzerland 5Institute of Risk Analysis, Prediction and Management (Risks-X), SUSTech, Shenzhen, China Nature is scary. You can be sitting at your home and next thing you know you are trapped under the ruble of your own house or sucked into a sinkhole. For millions of years we have been the figurines of this precarious scene and we have found our own ways of dealing with the anxiety. It is natural that we create and consume prophecies, conspiracies and false predictions. Information technologies amplify not only our rational but also irrational deeds. Social media algorithms, tuned to maximize attention, make sure that misinformation spreads much faster than its counterpart. What can we do to minimize the adverse effects of misinformation, especially in the case of earthquakes? One option could be to designate one authoritative institute, set up a big surveillance network and cancel or ban every source of misinformation before it spreads. This might have worked a few centuries ago but not in this day and age. Instead we propose a more inclusive option: embrace all voices and channel them into an actual, prospective earthquake prediction platform (Kamer et al. -
The Charles Walker Collection of Mystery, Myth and Magic the CHARLES WALKER COLLECTION LIST of CATEGORIES
The Charles Walker Collection of Mystery, Myth and Magic THE CHARLES WALKER COLLECTION LIST OF CATEGORIES ACUPUNCTURE AUTOMATA FLOWER REMEDIES MAGIC SYMBOLS RENNES-LE-CHATEAU AFRICAN ARTEFACTS AURA FLOWERS MAGIC ROBIN HOOD AND MAGIC AUTOMATIC WRITING FORTUNE STICKS MAGICAL CLOTHING ROMAN MYTHOLOGY AGES OF MAN FORTUNE TELLING MAGICAL RITUAL OBJECTS ROSICRUCIAN ALBEROBELLO BABYLONIAN MYTHS FRANCE MAGICIANS & INVOCATIONS RUNES ALCHEMY BARROWS FRANKENSTEIN MAGIC SPHERES ALPHABETS (MAGICAL) BEAUTY TREATMENTS FRENCH MYTHOLOGY MAJORCA SAINTS AMULETS BELGIUM MALAYSIA SCIENCE FICTION ANGELS BIOENERGY GAMES MALTA (PREHISTORIC & HORROR MAGS ANIMALS (BIRDS, FISH BLACK MAGIC GARGOYLES TEMPLES) SCIENTIFIC CURIOSITIES AND BEASTS) BLACK VIRGIN GEMS AND STONES MANDALAS SCREAMING SKULLS ANTHROPOSOPHY BRITAIN GEOMANCY MAORI MYTH SCRYING ARTHURIAN BRITISH MYTHS GERMANY MASKS SEANCES AROMATHERAPY BUDDHISM GHOSTS MASONS SEASONS ASTRAL AND ETHERIC BURMESE MYTHS GHOSTLY DOGS & MASSAGE SERPENT POWER ASTROLOGY: BLACK DOGS MAZES SHAKESPEARE AMERICAN (USA) CABBALA GIANTS MEDICAL SHAMAN ASTROLOGY CANDLE MAGIC GLASTONBURY MEDITATION SHEELA-NA-GIG ARABIC ASTROLOGY CARTOMANCY GOLDEN DAWN (ORDER OF) MERMAIDS & MERMEN SICILY ASTROLABES CATHARS & ALBIGENSIANS GOTHIC METAMORPHIC TECHNIQUE SIMULACRA ASTROLOGERS CATS (included in ANIMALS) GRAPHOLOGY MEXICAN ARCHAEOILOGY SKULLS ASTROLOGY (GENERAL) CAVE ART GRAVEYARDS MEXICAN MYTHOLOGY SNAKE CHARMERS BRITISH ASTROLOGY CELTIC GREECE MEXICO SPACE MEN CALENDARS CELTIC HEADS GREEK MYTHOLOGY MINORCA (ARCHAEOLOGY) SPAIN CHARTS (see -
Reliability Engineering: Trends, Strategies and Best Practices
Reliability Engineering: Trends, Strategies and Best Practices WHITE PAPER September 2007 Predictive HCL’s Predictive Engineering encompasses the complete product life-cycle process, from concept to design to prototyping/testing, all the way to manufacturing. This helps in making decisions early Engineering in the design process, perfecting the product – thereby cutting down cycle time and costs, and Think. Design. Perfect! meeting set reliability and quality standards. Reliability Engineering: Trends, Strategies and Best Practices | September 2007 TABLE OF CONTENTS Abstract 3 Importance of reliability engineering in product industry 3 Current trends in reliability engineering 4 Reliability planning – an important task 5 Strength of reliability analysis 6 Is your reliability test plan optimized? 6 Challenges to overcome 7 Outsourcing of a reliability task 7 About HCL 10 © 2007, HCL Technologies. Reproduction Prohibited. This document is protected under Copyright by the Author, all rights reserved. Reliability Engineering: Trends, Strategies and Best Practices | September 2007 Abstract In reliability engineering, product industries now follow a conscious and planned approach to effectively address multiple issues related to product certification, failure returns, customer satisfaction, market competition and product lifecycle cost. Today, reliability professionals face new challenges posed by advanced and complex technology. Expertise and experience are necessary to provide an optimized solution meeting time and cost constraints associated with analysis and testing. In the changed scenario, the reliability approach has also become more objective and result oriented. This is well supported by analysis software. This paper discusses all associated issues including outsourcing of reliability tasks to a professional service provider as an alternate cost-effective option. Importance of reliability engineering in product industry The degree of importance given to the reliability of products varies depending on their criticality. -
Prediction in Multilevel Generalized Linear Models
J. R. Statist. Soc. A (2009) 172, Part 3, pp. 659–687 Prediction in multilevel generalized linear models Anders Skrondal Norwegian Institute of Public Health, Oslo, Norway and Sophia Rabe-Hesketh University of California, Berkeley, USA, and Institute of Education, London, UK [Received February 2008. Final revision October 2008] Summary. We discuss prediction of random effects and of expected responses in multilevel generalized linear models. Prediction of random effects is useful for instance in small area estimation and disease mapping, effectiveness studies and model diagnostics. Prediction of expected responses is useful for planning, model interpretation and diagnostics. For prediction of random effects, we concentrate on empirical Bayes prediction and discuss three different kinds of standard errors; the posterior standard deviation and the marginal prediction error standard deviation (comparative standard errors) and the marginal sampling standard devi- ation (diagnostic standard error). Analytical expressions are available only for linear models and are provided in an appendix. For other multilevel generalized linear models we present approximations and suggest using parametric bootstrapping to obtain standard errors. We also discuss prediction of expectations of responses or probabilities for a new unit in a hypotheti- cal cluster, or in a new (randomly sampled) cluster or in an existing cluster. The methods are implemented in gllamm and illustrated by applying them to survey data on reading proficiency of children nested in schools. Simulations are used to assess the performance of various pre- dictions and associated standard errors for logistic random-intercept models under a range of conditions. Keywords: Adaptive quadrature; Best linear unbiased predictor (BLUP); Comparative standard error; Diagnostic standard error; Empirical Bayes; Generalized linear mixed model; gllamm; Mean-squared error of prediction; Multilevel model; Posterior; Prediction; Random effects; Scoring 1. -
A Philosophical Treatise of Universal Induction
Entropy 2011, 13, 1076-1136; doi:10.3390/e13061076 OPEN ACCESS entropy ISSN 1099-4300 www.mdpi.com/journal/entropy Article A Philosophical Treatise of Universal Induction Samuel Rathmanner and Marcus Hutter ? Research School of Computer Science, Australian National University, Corner of North and Daley Road, Canberra ACT 0200, Australia ? Author to whom correspondence should be addressed; E-Mail: [email protected]. Received: 20 April 2011; in revised form: 24 May 2011 / Accepted: 27 May 2011 / Published: 3 June 2011 Abstract: Understanding inductive reasoning is a problem that has engaged mankind for thousands of years. This problem is relevant to a wide range of fields and is integral to the philosophy of science. It has been tackled by many great minds ranging from philosophers to scientists to mathematicians, and more recently computer scientists. In this article we argue the case for Solomonoff Induction, a formal inductive framework which combines algorithmic information theory with the Bayesian framework. Although it achieves excellent theoretical results and is based on solid philosophical foundations, the requisite technical knowledge necessary for understanding this framework has caused it to remain largely unknown and unappreciated in the wider scientific community. The main contribution of this article is to convey Solomonoff induction and its related concepts in a generally accessible form with the aim of bridging this current technical gap. In the process we examine the major historical contributions that have led to the formulation of Solomonoff Induction as well as criticisms of Solomonoff and induction in general. In particular we examine how Solomonoff induction addresses many issues that have plagued other inductive systems, such as the black ravens paradox and the confirmation problem, and compare this approach with other recent approaches. -
Channeling: Brief History and Contemporary Context
Channeling: Brief History and Contemporary Context Although the term is new, channeling has been around for centuries. Its essence is hassle-free religion. One gains meaning in life and escape from anxiety from pre- digested 'wisdom' without any commit- ment or sacrifice. James E. Alcock POON-BENDING is out; channeling is in. This latest psychic craze is being embraced by many thousands of sincere believers, enlightening Stheir minds and often lightening their pocketbooks. "Channeling" describes what supposedly occurs when an individual serves as a conduit for some otherworldly entity to communicate with people of this world. It can take many forms: The channeler might be wide awake, in a trance, or even asleep ("dream channeling"). The channeler may speak or produce automatic writing, or even operate through a Ouija board. Channeling is essentially the mediumship of the late nineteenth and early twentieth centuries dressed up in new clothes. Parapsychologists realize this too. They have shown a remarkable lack of interest in the channelers' claims. Most parapsychologists consider the channeled communications to be simply the product of the channeler's mind and experience (Anderson 1988). The immortal entities who take advantage of the sudden abundance of channelers to speak to the people of this world most often bear names of a biblical or a mythic quality: Archangel Michael, Moses, the Invisibles, Ramtha, and even Jesus, are examples. Despite the erstwhile obscurity of many of the entities, they have been able to propel the people who channel them into some fame and often considerable fortune. For example, Penny Torres, a California housewife, was rocketed into prominence by channeling a 2,000-year-old man called Mafu, who teaches that humanoid colonies live under the earth and that extraterrestrials live among us. -
Inpresence 0022: the Real Magic of Uri Geller with Jeffrey Mishlove Video Transcript - New Thinking Allowed with Jeffrey Mishlove
InPresence 0022: The Real Magic of Uri Geller with Jeffrey Mishlove Video Transcript - New Thinking Allowed with Jeffrey Mishlove www.newthinkingallowed.org Recorded on March 12, 2018 Published to YouTube on March 23, 2018 Copyright © 2020, New Thinking Allowed Foundation (00:38) Hello, I’m Jeffrey Mishlove and today I’d like to talk about one of the most controversial figures in the field of 20th century parapsychology. I’m speaking of the Israeli psychic Uri Geller. I’ve known Uri ever since I’ve sponsored his first major public appearance in the United States back in 1973. We filled Zellerbach Auditorium at the University of California, Berkeley, to overflowing. I’ve had a relationship with Uri ever since then. I consider him a friend. Our relationship hasn't always been smooth, but I regard him as a person of great talent. (01:24) Now, many people have accused Uri of fraud. The list goes on and on and on. Frankly, that's true of virtually everybody who has exhibited or proclaimed marco-psychokinetic abilities. It's mind-boggling and for some people it just has to be fraud. I can tell you this: I have witnessed firsthand in a number of instances exhibits that I regard as valid demonstrations of macro-psychokinesis. And, I have many reports from other people, including researchers. (02:07) Now, many of you may not know, Uri was a rage back in the 1970s because he would go on public television and he could do simple little experiments, or tricks if you will - spoon bending, metal bending, fork bending. -
Some Statistical Models for Prediction Jonathan Auerbach Submitted In
Some Statistical Models for Prediction Jonathan Auerbach Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2020 © 2020 Jonathan Auerbach All Rights Reserved Abstract Some Statistical Models for Prediction Jonathan Auerbach This dissertation examines the use of statistical models for prediction. Examples are drawn from public policy and chosen because they represent pressing problems facing U.S. governments at the local, state, and federal level. The first five chapters provide examples where the perfunctory use of linear models, the prediction tool of choice in government, failed to produce reasonable predictions. Methodological flaws are identified, and more accurate models are proposed that draw on advances in statistics, data science, and machine learning. Chapter 1 examines skyscraper construction, where the normality assumption is violated and extreme value analysis is more appropriate. Chapters 2 and 3 examine presidential approval and voting (a leading measure of civic participation), where the non-collinearity assumption is violated and an index model is more appropriate. Chapter 4 examines changes in temperature sensitivity due to global warming, where the linearity assumption is violated and a first-hitting-time model is more appropriate. Chapter 5 examines the crime rate, where the independence assumption is violated and a block model is more appropriate. The last chapter provides an example where simple linear regression was overlooked as providing a sensible solution. Chapter 6 examines traffic fatalities, where the linear assumption provides a better predictor than the more popular non-linear probability model, logistic regression. -
The Case of Astrology –
The relation between paranormal beliefs and psychological traits: The case of Astrology – Brief report Antonis Koutsoumpis Department of Behavioral and Social Sciences, Vrije Universiteit Amsterdam Author Note Antonis Koutsoumpis ORCID: https://orcid.org/0000-0001-9242-4959 OSF data: https://osf.io/62yfj/?view_only=c6bf948a5f3e4f5a89ab9bdd8976a1e2 I have no conflicts of interest to disclose Correspondence concerning this article should be addressed to: De Boelelaan 1105, 1081HV Amsterdam, The Netherlands. Email: [email protected] The present manuscript briefly reports and makes public data collected in the spring of 2016 as part of my b-thesis at the University of Crete, Greece. The raw data, syntax, and the Greek translation of scales and tasks are publicly available at the OSF page of the project. An extended version of the manuscript (in Greek), is available upon request. To the best of my knowledge, this is the first public dataset on the astrological and paranormal beliefs in Greek population. Introduction The main goal of this work was to test the relation between Astrological Belief (AB) to a plethora of psychological constructs. To avoid a very long task, the study was divided into three separate studies independently (but simultaneously) released. Study 1 explored the relation between AB, Locus of Control, Optimism, and Openness to Experience. Study 2 tested two astrological hypotheses (the sun-sign and water-sign effects), and explored the relation between personality, AB, and zodiac signs. Study 3 explored the relation between AB and paranormal beliefs. Recruitment followed both a snowball procedure and it was also posted in social media groups of various Greek university departments. -
Prediction in General Relativity
Synthese (2017) 194:491–509 DOI 10.1007/s11229-015-0954-3 ORIGINAL RESEARCH Prediction in general relativity C. D. McCoy1 Received: 2 July 2015 / Accepted: 17 October 2015 / Published online: 27 October 2015 © Springer Science+Business Media Dordrecht 2015 Abstract Several authors have claimed that prediction is essentially impossible in the general theory of relativity, the case being particularly strong, it is said, when one fully considers the epistemic predicament of the observer. Each of these claims rests on the support of an underdetermination argument and a particular interpretation of the concept of prediction. I argue that these underdetermination arguments fail and depend on an implausible explication of prediction in the theory. The technical results adduced in these arguments can be related to certain epistemic issues, but can only be misleadingly or mistakenly characterized as related to prediction. Keywords Prediction · General theory of relativity · Theory interpretation · Global spacetime structure 1 Introduction Several authors have investigated the subject of prediction in the general theory of relativity (GTR), arguing on the strength of various technical results that making predictions is essentially impossible for observers in the spacetimes permitted by the theory (Geroch 1977; Hogarth 1993, 1997; Earman 1995; Manchak 2008). On the face of it, such claims seem to be in significant tension with the important successful predictions made on the theoretical basis of GTR. The famous experimental predictions of the precession of the perihelion of Mercury and of gravitational lensing, for example, are widely understood as playing a significant role in the confirmation of the theory (Brush 1999). Well-known relativist Clifford Will observes furthermore that “today, B C. -
CHAPTER 1 Promo
CHAPTER 1 WE ARE VIBRATIONAL BEINGS LIVING IN A VIBRATION UNIVERSE There is an orderliness in the universe, there is an unalterable law governing everything and every being that exists or lives. It is no blind law; for no blind law can govern the conduct of living beings. -Mahatma Gandhi- Vibration in The Universe The noted British physicist David Bohm (1917- 1992) believed in the unseen unity of all matter. He was convinced that our thoughts are part of the unified field of the universe. Bohm was one of the first physicists to state that there is an implicate order to the universe. He also stated, based on his understanding of quantum entanglement, that our 1 thoughts are part of the collective energy in the universe. The latest research tends to support that our reality is affected by our thoughts, and our connection to the collective field of energy is present throughout the universe. In essence, we are part of that field of energy. The energy that makes up the universe is within us, as well as being all around us. So, what is this “collective field” concept that scientists keep talking about? The Field One of the first books I studied on the subject was Lynne McTaggart’s The Field, published originally in Great Britain in 2001. The updated version published in 2008 made its way to the market in the United States. Being fond of audio books, when I listened to it my interest was so piqued, I also bought a hard copy. I often do this so I can go back to revisit something I found interesting in the audio book and want to study more carefully.