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34754 results in Cambridge Textbooks

Page 1627 of 1738

  • Book II

  • from On Moral Ends
  • Marcus Tullius Cicero
  • Edited by Julia Annas, University of Arizona
  • Translated by Raphael Woolf, Harvard University, Massachusetts
  • Book:
    Cicero: On Moral Ends
    Published online:
    05 June 2012
    Print publication:
    13 August 2001, pp 26-64

  • Summary

    (1) At this point they both looked at me and signalled that they were ready to hear me. I began by saying, ‘Let me first of all beg you not to expect me to expound a formal lecture to you like a philosopher. Indeed this is a procedure I have never greatly approved of even in the case of philosophers. After all, when did Socrates, who may justly be called the father of philosophy, ever do such a thing? It was, rather, the method of those known at the time as sophists. Gorgias of Leontini was the first of their number bold enough, at a public meeting, to “invite questions”, that is, to ask anyone to name a topic for him to speak on. A daring venture – I would have called it impudent, had this procedure not been adopted later by our own philosophers.

    (2) ‘But we know from Plato that Gorgias and the other sophists were mocked by Socrates. Socrates’ own technique was to investigate his interlocutors by questioning them. Once he had elicited their opinions in this way, he would then respond to them if he had any view of his own. This method was abandoned by his successors, but Arcesilaus revived it and laid it down that anyone who wanted to hear him speak should not ask him questions but rather state their own opinion. Only then would he reply.

  • Introduction

  • Marcus Tullius Cicero
  • Edited by Julia Annas, University of Arizona
  • Translated by Raphael Woolf, Harvard University, Massachusetts
  • Book:
    Cicero: On Moral Ends
    Published online:
    05 June 2012
    Print publication:
    13 August 2001, pp ix-xxvii

  • Summary

    In June 45 Marcus Tullius Cicero composed On Moral Ends, a treatment in three dialogues, over five books, of fundamental issues of moral philosophy. The sixty-one year old Cicero, a Roman statesman with an eventful and distinguished career, had gone into political retirement during the ascendancy to supreme power of Julius Caesar after a turbulent period of civil war, in which Cicero had ended up on the losing side. His personal life had also fallen apart. In 46 he divorced Terentia, his wife of thirty years, and married his young ward Publilia. The marriage broke up less than a year later, partly because of Cicero's extreme sorrow at the death in childbirth of his much–loved daughter Tullia, together with her baby, in February 45. A productive writer, he decided to use his enforced and grief-stricken leisure to introduce educated Romans to major parts of the subject of philosophy in their own language, rather than leaving them to read the originals in Greek. On Moral Ends is the most theoretical of the works on moral philosophy, accompanied by more specialized discussions in On Duties and Tusculan Disputations and the more ‘applied’ Friendship, Old Age and Reputation.

    On Moral Ends is a substantial work of moral philosophy. There have been periods when it has been an influential part of the discourse of moral theory, and it has always been a valuable source for the three moral theories it discusses, those of Epicurus, the Stoics and Antiochus (the last a hybrid influenced by Aristotle).

  • Book IV

  • from On Moral Ends
  • Marcus Tullius Cicero
  • Edited by Julia Annas, University of Arizona
  • Translated by Raphael Woolf, Harvard University, Massachusetts
  • Book:
    Cicero: On Moral Ends
    Published online:
    05 June 2012
    Print publication:
    13 August 2001, pp 90-116

  • Summary

    (1) With that, Cato concluded his discourse. ‘For a theme so large and obscure’, I said, ‘your exposition was as accurate as it was lucid. Either I should altogether give up on the idea of responding, or else at least take some time out for reflection. In both its foundations and in the edifice itself Stoicism is a system constructed with great care; incorrectly, perhaps, though I do not yet dare pronounce on that point, but certainly elaborately. It is no easy task to come to grips with it.’

    ‘Is that so?’ Cato replied. ‘In court I see you, under this new law, delivering the case for the defence on the same day and finishing up within three hours. Do you think I am going to grant you a deferral in this case? Mind you, you will find your brief no sounder than some of those you occasionally manage to win. So handle this one in the same way. Others have, after all, dealt with the topic, as you have yourself often enough, so you cannot be lacking in material.’

    (2) To this I replied: ‘Steady on! I am not in the habit of mounting reckless attacks on the Stoics. I am by no means in complete agreement with them, but humility restrains me: there is so much in Stoicism that I barely understand.’ ‘I admit’, said Cato, ‘that there are some obscure elements.

  • 22 - Inductive Behavior as an Evasion of the Problem of Induction

  • from PROBABILITY APPLIED TO PHILOSOPHY
  • Ian Hacking, University of Toronto
  • Book:
    An Introduction to Probability and Inductive Logic
    Published online:
    05 June 2012
    Print publication:
    02 July 2001, pp 261-268

  • Summary

    The frequentist agrees that no reasons can be given for inductive inferences, but holds that reasons can be given for inductive behavior, using certain procedures based on the idea of confidence intervals.

    The Bayesian is able to attach personal probabilities, or degrees of belief, to individual propositions. The hard-line frequency dogmatist thinks that probabilities can be attached only to a series of events.

    Probability, says this dogmatist, just means the relative frequency of some kind of event produced by a chance setup. Or it refers to the propensity of a chance setup to produce events with a certain stable frequency. Or it refers to certain underlying symmetry properties.

    At any rate, we cannot talk sensibly about the probability of a single event, for that event either happens or does not happen. It has “probability” 0 or 1, and that is that.

    So the frequency dogmatist will never talk about the frequency-type probability that a particular hypothesis is true.

    The hypothesis is either true or false, and there is no frequency about it. At most, we can discuss the relative frequency with which hypotheses of a certain kind are true.

    Thus far the dogmatic frequentist is happy to agree with Hume.

    INDUCTIVE BEHAVIOR

    Nevertheless, continues the frequentist, we may sometimes be able to apply a system for making inferences or drawing conclusions such that the conclusions are usually right.

    We can talk about the relative frequency with which inferences drawn by a certain method are in fact correct.

  • 1 - Logic

  • from LOGIC
  • Ian Hacking, University of Toronto
  • Book:
    An Introduction to Probability and Inductive Logic
    Published online:
    05 June 2012
    Print publication:
    02 July 2001, pp 1-10

  • Summary

    Logic is about good and bad reasoning. In order to talk clearly about reasoning, logicians have given precise meanings to some ordinary words. This chapter is a review of their language.

    ARGUMENTS

    Logicians attach a special sense to the word argument. In ordinary language, it usually takes two to argue. One dictionary defines an argument as:

  • A quarrel.

  • A discussion in which reasons are put forward in support of and against a proposition, proposal, or case.

  • A point or series of reasons presented to support a proposition which is the conclusion of the argument.

    • Definition (3) is what logicians mean by an argument.

    Reasoning is stated or written out in arguments. So logicians study arguments (in sense 3).

    An argument thus divides up into:

    A point or series of reasons which are called premises, and a conclusion.

    Premises and conclusion are propositions, statements that can be either true or false. Propositions are “true-or-false.”

    GOING WRONG

    The premises are supposed to be reasons for the conclusion. Logic tries to understand the idea of a good reason.

    We find arguments convincing when we know that the premises are true, and when we see that they give a good reason for the conclusion.

    So two things can go wrong with an argument:

  • ▪ the premises may be false.

  • ▪ the premises may not provide a good reason for the conclusion.

  • 20 - The Philosophical Problem of Induction

  • from PROBABILITY APPLIED TO PHILOSOPHY
  • Ian Hacking, University of Toronto
  • Book:
    An Introduction to Probability and Inductive Logic
    Published online:
    05 June 2012
    Print publication:
    02 July 2001, pp 247-255

  • Summary

    For philosophers, this is the most important question about induction. It is not a problem within inductive logic. It questions the very possibility of inductive reasoning itself.

    DAVID HUME

    In 1739, David Hume (1711–1776), the Scottish philosopher, published A Treatise of Human Nature, one of the half-dozen most influential books of Western philosophy. He was twenty-eight years old at the time. In 1748, he published An Enquiry Concerning Human Understanding.

    These books, especially the second, include the classic statement of what came to be called the problem of induction.

    Hume's problem about induction is only a small part of a very general theory of knowledge. Here we study just this one aspect of Hume's philosophy.

    SKEPTICISM

    In ordinary English, a skeptic is:

  • ♦ Someone who habitually doubts accepted beliefs.

  • ♦ A person who mistrusts other people or their ideas.

  • ♦ Someone who rejects traditional beliefs, such as religious beliefs.

    • PHILOSOPHICAL SKEPTICISM

    Philosophers attach a far more sweeping sense to the idea of skepticism. A philosophical skeptic is someone who claims to:

  • ♦ Doubt that any real knowledge or sound belief about anything is possible.

    • There are more specialized types of philosophical skepticism, depending upon what kind of knowledge is in doubt. Think of any field of knowledge or belief X, where X may be religious, or scientific, or moral. X may be knowledge about other people, or about the reality of the world around us, or even knowledge about yourself.

An Introduction to Probability and Inductive Logic
  • Ian Hacking
  • Published online:
    05 June 2012
    Print publication:
    02 July 2001
  • This is an introductory 2001 textbook on probability and induction written by one of the world's foremost philosophers of science. The book has been designed to offer maximal accessibility to the widest range of students (not only those majoring in philosophy) and assumes no formal training in elementary symbolic logic. It offers a comprehensive course covering all basic definitions of induction and probability, and considers such topics as decision theory, Bayesianism, frequency ideas, and the philosophical problem of induction. The key features of this book are a lively and vigorous prose style; lucid and systematic organization and presentation of ideas; many practical applications; a rich supply of exercises drawing on examples from such fields as psychology, ecology, economics, bioethics, engineering, and political science; numerous brief historical accounts of how fundamental ideas of probability and induction developed; and a full bibliography of further reading.

  • 14 - Coherence

  • from PROBABILITY AS A MEASURE OF BELIEF
  • Ian Hacking, University of Toronto
  • Book:
    An Introduction to Probability and Inductive Logic
    Published online:
    05 June 2012
    Print publication:
    02 July 2001, pp 163-170

  • Summary

    Consistent personal betting rates satisfy the basic rules of probability. Consistency in this sense is called coherence.

    Personal probabilities and betting rates are all very well. But thus far they have no structure, no rules–in fact, not much meaning. Now we give one argument that betting rates ought to satisfy the basic rules for probability. We have already had three thought experiments in Chapter 13. Here are two more.

    FOURTH THOUGHT EXPERIMENT: SETS OF BETTING RATES

    A group of beliefs can be represented by a set of betting rates.

    Imagine yourself advertising a set of betting rates. For each of the propositions A, B, … K in the set, you offer betting rates pa, pb, pc , …, pk .

    In this imaginary game, you are prepared to bet, say,

    on A at rate pa , or

    against A at rate (1–pa ).

    FIFTH THOUGHT EXPERIMENT: SIMPLE INCONSISTENCY

    These are personal betting rates. Couldn't you choose any fractions you like?

    Of course. But you might be inconsistent.

    For example, suppose you are concerned with just two possibilities, B (for “below zero”) and ~B:

    B: On the night of next March 21, the temperature will fall below 0°C at the Toronto International Airport meteorological station.

    ~B: On the night of next March 21, the temperature will not fall below 0°C at the Toronto International Airport meteorological station.

  • 17 - Normal Approximations

  • from PROBABILITY AS FREQUENCY
  • Ian Hacking, University of Toronto
  • Book:
    An Introduction to Probability and Inductive Logic
    Published online:
    05 June 2012
    Print publication:
    02 July 2001, pp 201-208

  • Summary

    We have seen that relative frequencies converge on theoretical probabilities. But how fast? When can we begin to use an observed relative frequency as a reliable estimate of a probability? This chapter gives some answers. They are a little more technical than most of this book. For practical purposes, all you need to know is how to use is the three boxed Normal Facts below.

    EXPERIMENTAL BELL-SHAPED CURVES

    On page 191 we had the result of a coin-tossing experiment. The graph was roughly in the shape of a bell. Many observed distributions have this property.

    Example: Incomes. In modern industrialized countries we have come to expect income distributions to look something like Curve 1 on the next page, with a few incredibly rich people at the right end of the graph. But in feudal times there was no middle class, so we would expect the income distribution in Curve 2. It is “bimodal”–it has two peaks.

    Example: Errors. We can never measure with complete accuracy. Any sequence of “exact” measurements of the same quantity will show some variation. We often average the results. We can think of this as a sample mean. A good measuring device will produce results that cluster about the mean, with a small sample standard deviation. A bad measuring device gives results that vary wildly from one another, giving a large standard deviation.

  • 5 - Conditional Probability

  • from HOW TO CALCULATE PROBABILITIES
  • Ian Hacking, University of Toronto
  • Book:
    An Introduction to Probability and Inductive Logic
    Published online:
    05 June 2012
    Print publication:
    02 July 2001, pp 47-57

  • Summary

    The most important new idea about probability is the probability that something happens, on condition that something else happens. This is called conditional probability.

    CATEGORICAL AND CONDITIONAL

    We express probabilities in numbers. Here is a story I read in the newspaper. The old tennis pro Ivan was discussing the probability that the rising young star Stefan would beat the established player Boris in the semifinals. Ivan was set to play Pete in the other semifinals match. He said,

    The probability that Stefan will beat Boris is 40%.

    Or he could have said,

    The chance of Stefan's winning is 0.4.

    These are categorical statements, no ifs and buts about them. Ivan might also have this opinion:

    Of course I'm going to win my semifinal match, but if I were to lose, then Stefan would not be so scared of meeting me in the finals, and he would play better; there would then be a 50–50 chance that Stefan would beat Boris.

    This is the probability of Stefan's winning in his semifinal match, conditional on Ivan losing the other semifinal. We call it the conditional probability. Here are other examples:

    Categorical: The probability that there will be a bumper grain crop on the prairies next summer.

    Conditional: The probability that there will be a bumper grain crop next summer, given that there has been very heavy snowfall the previous winter. […]

Page 1627 of 1738