From Certainty To Uncertainty

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The Certainty of Uncertainty

Author: Mark Schaefer
language: en
Publisher: Wipf and Stock Publishers
Release Date: 2018-08-23
The world is full of people who are very certain--in politics, in religion, in all manner of things. In addition, political, religious, and social organizations are marketing certainty as a cure all to all life's problems. But is such certainty possible? Or even good? The Certainty of Uncertainty explores the question of certainty by looking at the reasons human beings crave certainty and the religious responses we frequently fashion to help meet that need. The book takes an in-depth view of religion, language, our senses, our science, and our world to explore the inescapable uncertainties they reveal. We find that the certainty we crave does not exist. As we reflect on the unavoidable uncertainties in our world, we come to understand that letting go of certainty is not only necessary, it's beneficial. For, in embracing doubt and uncertainty, we find a more meaningful and courageous religious faith, a deeper encounter with mystery, and a way to build strong relationships across religious and philosophical lines. In The Certainty of Uncertainty, we see that embracing our belief systems with humility and uncertainty can be transformative for ourselves and for our world.
From Certainty to Uncertainty

Early theorists believed that in science lay the promise of certainty. Built on a foundation of fact and constructed with objective and trustworthy tools, science produced knowledge. But science has also shown us that this knowledge will always be fundamentally incomplete and that a true understanding of the world is ultimately beyond our grasp. In this thoughtful and compelling book, physicist F. David Peat examines the basic philosophic difference between the certainty that characterized the thinking of humankind through the nineteenth century and contrasts it with the startling fall of certainty in the twentieth. The nineteenth century was marked by a boundless optimism and confidence in the power of progress and technology. Science and philosophy were on firm ground. Newtonian physics showed that the universe was a gigantic clockwork mechanism that functioned according to rigid laws "that its course could be predicted with total confidence far into the future. Indeed, in 1900, the President of the Royal Society in Britain went so far as to proclaim that everything of importance had already been discovered by science. But it was not long before the seeds of a scientific revolution began to take root. Quantum Theory and the General Theory of Relativity exploded the clockwork universe, proving beyond a shadow of a doubt that our knowledge was, at best, incomplete "and would probably remain that way forever. There were places in the universe, such as black holes, from which no information at all could ever be obtained. Chaos Theory also demonstrated our inherent limits to knowing, predicting, and controlling the world around us and showed the way that chaos can often be found at the heart of natural and social systems. Although we may not always recognize it, this new world view has had a profound effect not only on science, but on art, literature, philosophy, and societal relations. The twenty-first century now begins with a humble acceptance of uncertainty. From Certainty to Uncertainty traces the rise and fall of the deterministic universe and shows the evolving influences that such disparate disciplines now have on one another. Drawing on the lessons we can learn from history, Peat also speculates on how we will manage our lives into the future.
Between Certainty and Uncertainty

Author: Ludomir M. Laudański
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-10-14
„Between Certainty & Uncertainty” is a one-of–a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units: · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.