Introduction

Introduction

One of the most important topics in critical thinking is how to reason about chance and uncertainty. Human beings are prone to make mistakes in estimating the likelihood of events; in distinguishing meaningful correlations from mere coincidences; and in using probability information in drawing inferences and making decisions. Understanding some basic principles of reasoning with probabilities can help us be aware of these weaknesses in our reasoning.

Because probability is also a technical concept in mathematics and formal reasoning, it's easy to get bogged down in unnecessary technical details, which would not be helpful from a critical thinking perspective. My goal is not to make us experts in solving mathematical problems using probabilities.

My goal, rather,  is to help you develop "probability literacy" — a general sense of what probability is, the role it plays in our reasoning about the world, what mistakes we're prone to make, and what methods there may be to avoid those mistakes.

Probability is also deeply interesting from a philosophical perspective. It's not my primary focus in these lectures, but I do touch on some of these dimensions. I have found that the kind of probability literacy that I think is useful for critical thinking actually requires more background in the philosophy of probability than most mathematics students receive.

Thus, this material is divided into three parts.

Part 1: What is Probability? A gentle introduction to the philosophy of probability.

Part 2: The Logic of Probability. An introduction to the basic mathematical rules that govern correct reasoning with probabilities.

Part 3: Probability Fallacies. An introduction to errors that we're prone to make when reasoning about certain topics, e.g. coincidences, randomness, looking for causal explanations of probabilistic patterns, etc. 

This last section is incomplete, but there is still plenty here to chew on. My original outline had additional topics planned, but circumstances prevented me from completing them. I look forward to finishing this work at some point in the future. 

(1) Video Library > 7. Reasoning About Chance and Uncertainty: Philosophy, Rules and Fallacies

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Introduction

  • Introduction

Part 1: What is Probability?: A Gentle Introduction to the Philosophy of Probability

  • Introduction

What is Probability?

  • Probability: Why Learn This Stuff?
  • What is Inductive Logic?
  • Probability as a Mathematical Object vs What That Object Represents

Interpretations of Probability

  • Classical Probability
  • Logical Probability
  • Frequency Interpretations
  • Subjective (Bayesian) Probability
  • Propensity Interpretations

Part 2: The Logic of Probability: Introduction to the Basic Rules

  • Introduction

Preliminary Concepts

  • What Has a Probability? Propositions versus Events
  • Probabilities Range Between 0 and 1
  • Mutually Exclusive Events
  • Independent Events

The Basic Rules

  • The Negation Rule: P(not-A)

Disjunction Rules: P(A or B)

  • Restricted Disjunction Rule: P(A or B) = P(A) + P(B)
  • General Disjunction Rule: P(A or B) = P(A) + P(B) - P(A and B)

Conjunction Rules: P(A and B)

  • Restricted Conjunction Rule: P(A and B) = P(A) x P(B)
  • General Conjunction Rule: P(A and B) = P(A) x P(B|A)

Conditional Rules: P(A given B)

  • Conditional Probability Rule
  • Total Probability Rule
  • Bayes’ Rule

Part 3: Probability Fallacies: Understanding the Errors We Make When Reasoning About Chance and Uncertainty

  • Introduction

Coincidences: When the Impossible Becomes Inevitable

  • Introduction
  • The Basic Fallacy
  • Borel's Law: Understanding Impossible Events
  • How to Create the Illusion of Miraculous Predictive Power
  • The Birthday Problem, Lottery Coincidences and the Power of Very Large Numbers

The Gambler's Fallacy: Bias, Randomness and the Illusion of Control

  • Introduction
  • The Basic Fallacy
  • Fairness, Bias and Independence
  • How Can You Tell Whether a Chance Setup is Unfair?
  • The Physics of Coin Tosses
  • Casino Games: Why the House Always Wins
  • Cognitive Factors and the Psychology of Gambling

Small Sample Fallacies: Looking for Causes of Extreme Cases

  • The Small Sample Fallacy: Looking for Causes of Statistical Artifacts