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Logic and Conditional Probability

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Probability and Conditional Expectation

Probability and Conditional Expectations bridges the gap between books on probability theory and statistics by providing the probabilistic;

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Logic with a Probability Semantics

semantics for logic is replaced with one based more on probability, and where values ranging from 0 to 1 are subject to probability axioms. Moreover;

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Conditional Measures and Applications

, conditional probability was relegated to scattered journal articles and mere chapters in larger works on probability. This second edition continues to;

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Probability

distribution, and limits * An early introduction to random variables and Monte Carlo simulation and an emphasis on conditional probability;

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The Epistemology of Indicative Conditionals

do we learn when we receive new conditional information? In answering these questions, this book combines the formal tools of logic and;

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The Epistemology of Indicative Conditionals

do we learn when we receive new conditional information? In answering these questions, this book combines the formal tools of logic and;

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First Course in Probability

: Combinatorial Analysis; Axioms of Probability; Conditional Probability and Independence; Random Variables; Continuous Random Variables; Jointly;

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Intermediate Probability Theory for Biomedical Engineers

This is the second in a series of three short books on probability theory and random processes for biomedical engineers. This volume;

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New types of Neutrosophic Set/Logic/Probability, Neutrosophic Over-/Under-/Off-Set, Neutrosophic Refined Set, and their Extension to Plithogenic Set/Logic/Probability, with Applications

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Probability Concepts in Engineering Planning and Design

Distribution 3.2.10. The Beta Distribution 3.2.11. Other Distributions 3.3. Multiple Random Variables 3.3.1. Joint and Conditional Probability;

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Mathematics of Probability

This book covers the basics of modern probability theory. It begins with probability theory on finite and countable sample spaces and then;

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Stochastic Processes

processes. Subsequent chapters examine conditional probability and conditional expectation, normal processes and covariance stationary processes;

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Probability Logics

interest is mathematical techniques for infinitary probability logics used to obtain results about proof-theoretical and model-theoretical issues;

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Basic Stochastic Processes

provides a detailed treatment of conditional expectation and probability, a topic that in principle belongs to probability theory, but is essential;

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Introduction to Probability Theory with Contemporary Applications

and clear examples, written in plain language, expose students to the rules and methods of probability. Suitable for an introductory;

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Defeasible Deontic Logic

classical deontic logic does of prima facie obligation, conditional obligation, and priorities of normative principles.;

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Safety Aspects of Nuclear Power Plants in Human Induced External Events

probability and the conditional probability of spent fuel damage. In the most elaborated stage, probabilistic safety assessment (PSA) techniques are;

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Everything that Linguists have Always Wanted to Know about Logic . . . But Were Ashamed to Ask

quantifiers, and fuzzy logic-with new material on the logic of conditional sentences, linguistic applications of type theory, Anil Gupta's work on;

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Cambridge Studies in Probability, Induction and Decision Theory

advance offered by the book is a 'representation theorem' that shows that both causal decision theory and its main rival, Richard Jeffrey's logic;

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Cambridge Studies in Probability, Induction and Decision Theory

advance offered by the book is a 'representation theorem' that shows that both causal decision theory and its main rival, Richard Jeffrey's logic;

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Elementary Probability

subject demands. Topics covered include conditional probability, independence, discrete and continuous random variables, basic combinatorics;

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Elementary Probability

subject demands. Topics covered include conditional probability, independence, discrete and continuous random variables, basic combinatorics;

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Probability and Measure Theory

topics in analysis. It provides extensive coverage of conditional probability and expectation, strong laws of large numbers, martingale theory;

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Probability Theory and Statistical Applications

Conditional probability and independence One-dimensional random variables Functions of random variables Bi-dimensional random variables;

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Foundations of Probabilistic Logic Programming

The integration of logic and probability combines the capability of the first to represent complex relations among entities with the;

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Statistical Relational Artificial Intelligence

has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus;

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