From 44bf1a7a43137d997c7a371b8e8fd95d5adbe335 Mon Sep 17 00:00:00 2001 From: phidias Date: Wed, 11 Feb 2026 14:03:51 +0000 Subject: [PATCH] docs: create education/statistics/multivariate-distribution --- .../statistics/multivariate-distribution.html | 158 ++++++++++++++++++ 1 file changed, 158 insertions(+) create mode 100644 education/statistics/multivariate-distribution.html diff --git a/education/statistics/multivariate-distribution.html b/education/statistics/multivariate-distribution.html new file mode 100644 index 0000000..feaf2c5 --- /dev/null +++ b/education/statistics/multivariate-distribution.html @@ -0,0 +1,158 @@ + + +

General

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Symmetric

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If there is a point that,

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Then,

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Is the expectation of this random variable, equal to the point of symmetry.

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Median and Quantiles

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The middle value of the random variable.
For median, set p to 0.5.

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Variance

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A positive quantity that measures the spread of the distribution of the random variable about its mean value.
Larger values of the variance indicate that the distribution is more spread out.

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Covariance

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Independent random variables have a covariance of zero.

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Correlation

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Values between -1 and 1, and independent random variables have a correlation of zero.

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What if random variable X and Y have linear relationship, that is

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That is, 

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Distribution Function

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 DiscreteContinuous
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Probability

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A set of probability value pi assigned to each of the values taken by the discrete random variables xi.

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Probability Mass Function (PMF)

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Probability

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Expectation

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Probability Density Function (PDF)

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Probabilistic properties of a continuous random variable.

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Expectation

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Cumulative

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A set of probability value pi assigned to each of the values taken by the discrete random variables xi.

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Jointly Distributed +
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satisfying 

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satisfying 

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Joint Cumulative +
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Marginal Probability

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Obtained by summing or integrating the joint probability distribution over the values of the other random variable.

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Conditional Probability

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The probabilistic properties of the random variable X under the knowledge provided by the value of Y.

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Independence

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Two random variables X and Y are said to be independent if:

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for all values i of X and j of Y.

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for all X and Y.

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