Probability

Darrell P. Rowbottom

• Publisher: Polity
• Year: 2015
• Print ISBN: 9780745652573, 9780745652566
• eBook ISBN: 9781509500208
• Edition: 1
• Topic: Philosophy
• Subtopic: Epistemology in Philosophy

When a doctor tells you theres a one percent chance that an operation will result in your death, or a scientist claims that his theory is probably true, what exactly does that mean? Understanding probability is clearly very important, if we are to make good theoretical and practical choices.

In this engaging and highly accessible introduction to the philosophy of probability, Darrell Rowbottom takes the reader on a journey through all the major interpretations of probability, with reference to real-world situations. In lucid prose, he explores the many fallacies of probabilistic reasoning, such as the gamblers fallacy and the inverse fallacy, and shows how we can avoid falling into these traps by using the interpretations presented. He also illustrates the relevance of the interpretation of probability across disciplinary boundaries, by examining which interpretations of probability are appropriate in diverse areas such as quantum mechanics, game theory, and genetics.

Using entertaining dialogues to draw out the key issues at stake, this unique book will appeal to students and scholars across philosophy, the social sciences, and the natural sciences.

1
Probability: A Two-Faced Guide to Life?

1 Why Care about Probabilities?

A book on how to understand probability may not sound interesting; in fact, it probably doesn't sound interesting if you're not interested in maths. But if you don't understand probability, then you'll probably find yourself making some bad decisions. (Maybe it would pique your interest if I told you that I made a lot of money, from people who didn't know as much about probability as they should have, during my student days? More on this in Chapter 3.) Sometimes you'll act when you shouldn't, and other times you'll fail to act when you should. Don't take my word for it. Let's think about scenarios in which claims involving probabilities are relevant in everyday life.

Imagine you're intent on climbing a mountain, and you consult the weather forecast for the day. On the report, you see that the probability of precipitation in the relevant mountain range – or what is sometimes called the chance of rain – is just one in twenty, or 5 per cent. Should you take waterproof gear with you?

Obviously this will depend a little bit on context, so let's fill some of that out. Imagine you don't have any waterproof gear, and that it will be quite a hassle to get some, but that you don't want to get wet. Overall, you think that getting wet would be more unpleasant than going through the trouble of getting the gear; in an ideal world, however, you'd neither get the gear nor get wet. It's possible to assign a number to each possible outcome, a utility, to make this kind of discussion more precise. Let's avoid complicating things unnecessarily, though. We can instead rank the four possible outcomes in order of your preference: no gear and no rain (best), gear and rain (2nd best), gear and no rain (3rd best), and no gear and rain (worst). (It's always helpful in such scenarios to think about whether anything has been assumed which hasn't been explicitly mentioned. I encourage you to do this throughout the book. In this case, for example, ‘gear and rain’ has been ranked more highly than ‘gear and no rain’. I did this because I figured you'd be a bit irritated at having the gear if it didn't rain; you'd be thinking ‘I shouldn't have bothered to get this gear!’ But perhaps I should have added this as a stipulation in presenting the context.)

The order of preference makes it clearer what's at stake in this hypothetical scenario. If you take the gear, you miss out on the best possible outcome. But you also protect yourself from the worst possible outcome (while giving yourself a shot at the second and third best outcomes). Now if the order of preference were the only information you had, your choice might depend only on your attitude towards risk; some people are more risk-averse than others. But you also know that no rain is much more probable than rain, which may affect your decision. And indeed it should affect your decision, as we will soon see, when ‘much more probable’ is interpreted in some of the available ways. Very roughly, we may capture why by saying that probability is often used as a measure of the salience of various possibilities.

Maybe you are still unconvinced that probabilities, so construed, are important. So imagine that you failed to rank possibilities by salience. You would treat any possibility you identified the same as any other. You would treat the possibility of a meteorite landing on your head, or of being accosted by a knife-wielding psychopath, as seriously as you would the possibility of rain. You would be worried about whether to wear a hard hat, a stab-proof vest, and so forth. In fact, with a little imagination, you'd be worried about so many possible fates that you'd be overwhelmed and confused. (Of course, inaction can be bad too. If you stay in, you might die in an earthquake. And so on!) The only upside would be that you'd be able to consider lots of good possibilities as well as the bad ones; of stumbling on a hidden cache of diamonds, of meeting a future partner, and so forth. But really, you'd have no way of proceeding other than guessing about what was best to do. Life would be a series of such guesses. And most of us don't treat life that way, in so far as we think that anyone who wears a hard hat at all times is crazy.

However, this still leaves us with the question of what, exactly, we can and should understand probability talk to reflect. And this is the main question that this book ...

Table of contents

• Cover
• Key Concepts in Philosophy
• Title page
• Copyright page
• Dedication
• Preface
• 1: Probability: A Two-Faced Guide to Life?
• 2: The Classical Interpretation
• 3: The Logical Interpretation
• 4: The Subjective Interpretation
• 5: The Objective Bayesian Interpretation
• 6: Group Level Interpretations
• 7: The Frequency Interpretation
• 8: The Propensity Interpretation
• 9: Fallacies, Puzzles, and a Paradox
• 10: Probability in the Humanities, Natural Sciences, and Social Sciences
• Appendice A: The Axioms and Laws of Probability
• Appendice B: Bayes's Theorem
• References
• Index
• End User License Agreement