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gptkbp:instanceOf
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Probability Distribution
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gptkbp:alsoKnownAs
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gptkb:Normal_Distribution
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gptkbp:centralLimitTheorem
|
limit of sum of independent random variables
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gptkbp:characteristic
|
exp(iμt - 0.5σ^2 t^2)
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gptkbp:cumulativeDistributionFunction
|
Φ((x-μ)/σ)
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gptkbp:definedIn
|
real numbers
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gptkbp:describedBy
|
mean
standard deviation
variance
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gptkbp:describedYear
|
1809
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gptkbp:entropy
|
0.5*ln(2πeσ^2)
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gptkbp:firstDescribed
|
gptkb:Carl_Friedrich_Gauss
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gptkbp:hasSpecialCase
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gptkb:exponential_family
gptkb:elliptical_distribution
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gptkbp:hasType
|
gptkb:univariate_normal_distribution
gptkb:multivariate_normal_distribution
|
|
https://www.w3.org/2000/01/rdf-schema#label
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Gaussian Distribution
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gptkbp:kurtosis
|
3
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gptkbp:maximumLikelihoodEstimator
|
sample mean and sample variance
|
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gptkbp:meanSymbol
|
μ
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gptkbp:medium
|
mean
|
|
gptkbp:mode
|
mean
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gptkbp:momentGeneratingFunction
|
exp(μt + (σ^2 t^2)/2)
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gptkbp:parameter
|
mean
standard deviation
variance
|
|
gptkbp:probabilityDensityFunction
|
f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
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gptkbp:relatedTo
|
gptkb:probability_theory
gptkb:standard_normal_distribution
gptkb:student's_t-distribution
gptkb:Laplace_distribution
gptkb:chi-squared_distribution
gptkb:log-normal_distribution
gptkb:Gaussian_process
Gaussian noise
bell curve
error function
z-score
|
|
gptkbp:shape
|
bell curve
|
|
gptkbp:skewness
|
0
|
|
gptkbp:standardDeviationSymbol
|
σ
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|
gptkbp:supports
|
(-∞, ∞)
|
|
gptkbp:symmetry
|
symmetric about mean
|
|
gptkbp:usedIn
|
gptkb:machine_learning
gptkb:natural_sciences
gptkb:signal_processing
statistics
|
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gptkbp:varianceSymbol
|
σ^2
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gptkbp:bfsParent
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gptkb:Normal_Distribution
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gptkbp:bfsLayer
|
8
|