Characterizing the relationship between two quantitative variables X and Y Ricco Rakotomalala

Source URL: eric.univ-lyon2.fr

• Probability theory
• Statistical dependence
• Data analysis
• Covariance
• Variance
• Correlation and dependence
• Independence
• Expected value
• Sample mean and sample covariance
• Statistics
• Covariance and correlation
• Algebra of random variables

2009 Paper 7 Question 11 Information Theory and Coding (a) Let X and Y be discrete random variables over state ensembles {x} and {y} having probability distributions p(x) and p(y), conditional probability distributions

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2007 Paper 8 Question 7 Information Theory and Coding (a) Suppose that X is a random variable whose entropy H(X) is 8 bits. Suppose that Y (X) is a deterministic function that takes on a different value for each value o

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1997 Paper 8 Question 11 Information Theory and Coding The input source to a noisy communication channel is a random variable X over the four symbols a, b, c, d. The output from this channel is a random variable Y over

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2006 Paper 7 Question 8 Information Theory and Coding (a) Give three different expressions for mutual information I(X; Y ) between two discrete random variables X and Y , in terms of their two conditional entropies H(X|

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COMPUTER SCIENCE TRIPOS Part II – 2013 – Paper 9 6 Information Theory and Coding (JGD) (a) Two random variables X and Y are correlated. The marginal probabilities p(X) and p(Y ) are known, as is their joint probabili

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1998 Paper 8 Question 11 Information Theory and Coding Consider a binary symmetric communication channel, having source alphabet X = {0, 1} with probabilities {0.5, 0.5}. Its output alphabet is Y = {0, 1} and its channe

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Tomas Everaert Vrije Universiteit Brussel Monotone-light factorisation systems and torsion theories Given a torsion theory (Y, X) in an abelian category C, the reflector I : C → X to the torsion-free subcategory X indu

Source URL: web.science.mq.edu.au

2004 Paper 8 Question 10 Information Theory and Coding (a) Consider a binary symmetric communication channel, whose input source is the alphabet X = {0, 1} with probabilities {0.5, 0.5}; whose output alphabet is Y = {0,

Source URL: www.cl.cam.ac.uk

2006 Paper 8 Question 16 Information Theory and Coding (a) Suppose we know the conditional entropy H(X|Y ) for two slightly correlated discrete random variables X and Y . We wish to guess the value of X, from knowledge

Source URL: www.cl.cam.ac.uk

• Applied mathematics
• Fourier analysis
• Information theory
• Digital signal processing
• Sinc function
• Integral transforms
• Fourier transform
• Rectangular function
• Entropy
• Mathematical analysis
• Signal processing
• Mathematics