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William Feller: A Biography - Fachrichtung Mathematik
William Feller: A Biography - Fachrichtung Mathematik

Dowe2010_MML_Handboo.. - Clayton School
Dowe2010_MML_Handboo.. - Clayton School

Truncated variation - its properties and applications in stochastic
Truncated variation - its properties and applications in stochastic

Continuous Distributions
Continuous Distributions

... Understand concepts of the uniform distribution. Appreciate the importance of the normal distribution. Recognize normal distribution problems and know how to solve such problems. Decide when to use the normal distribution to approximately binomial distribution problems and know how to work such prob ...
To P or not to P: on the evidential nature of P
To P or not to P: on the evidential nature of P

An Introduction to Statistical Signal Processing
An Introduction to Statistical Signal Processing

The life and work of A.A. Markov
The life and work of A.A. Markov

Elements of Information Theory Second Edition Solutions to Problems
Elements of Information Theory Second Edition Solutions to Problems

On the Prime Number Subset of the Fibonacci Numbers
On the Prime Number Subset of the Fibonacci Numbers

... The Twin Prime Conjecture states that there are infinitely many primes p such that p + 2 is also prime. An example is (5,7). This is an unproven conjecture at this point; however, Brun used his sieve to show that the sum of the recipricals converges. Brun used his sieve to make progress on the conje ...
QUANTITATIVE LANDSLIDE HAZARD ASSESSMENT IN
QUANTITATIVE LANDSLIDE HAZARD ASSESSMENT IN

Looking for a needle in a haystack: inference about individual fitness
Looking for a needle in a haystack: inference about individual fitness

ON THE IMPLEMENTATION OF HUGE RANDOM OBJECTS 1
ON THE IMPLEMENTATION OF HUGE RANDOM OBJECTS 1

Measure Theoretic Probability P.J.C. Spreij (minor revisions by S.G.
Measure Theoretic Probability P.J.C. Spreij (minor revisions by S.G.

An Invitation to Sample Paths of Brownian Motion
An Invitation to Sample Paths of Brownian Motion

Measure Theoretic Probability P.J.C. Spreij
Measure Theoretic Probability P.J.C. Spreij

What Can the Duration of Discovered Cartels Tell Us About the
What Can the Duration of Discovered Cartels Tell Us About the

Distances between probability measures and coefficients of
Distances between probability measures and coefficients of

Computer arithmetic for probability distribution variables
Computer arithmetic for probability distribution variables

Mathematical Structures in Computer Science Shannon entropy: a
Mathematical Structures in Computer Science Shannon entropy: a

Shannon entropy: a rigorous mathematical notion at the
Shannon entropy: a rigorous mathematical notion at the

A Survey on Distribution Testing
A Survey on Distribution Testing

On Generalized Measures of Information with
On Generalized Measures of Information with

STPLAN Version 4.5: February, 2010 Calculations for Sample Sizes
STPLAN Version 4.5: February, 2010 Calculations for Sample Sizes

An Analysis of Random-Walk Cuckoo Hashing
An Analysis of Random-Walk Cuckoo Hashing

here for U12 text. - Iowa State University
here for U12 text. - Iowa State University

1 2 3 4 5 ... 262 >

Inductive probability

Inductive probability attempts to give the probability of future events based on past events. It is the basis for inductive reasoning, and gives the mathematical basis for learning and the perception of patterns. It is a source of knowledge about the world.There are three sources of knowledge: inference, communication, and deduction. Communication relays information found using other methods. Deduction establishes new facts based on existing facts. Only inference establishes new facts from data.The basis of inference is Bayes' theorem. But this theorem is sometimes hard to apply and understand. The simpler method to understand inference is in terms of quantities of information.Information describing the world is written in a language. For example a simple mathematical language of propositions may be chosen. Sentences may be written down in this language as strings of characters. But in the computer it is possible to encode these sentences as strings of bits (1s and 0s). Then the language may be encoded so that the most commonly used sentences are the shortest. This internal language implicitly represents probabilities of statements.Occam's razor says the ""simplest theory, consistent with the data is most likely to be correct"". The ""simplest theory"" is interpreted as the representation of the theory written in this internal language. The theory with the shortest encoding in this internal language is most likely to be correct.
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