docs: update education/statistics/random-variable
This commit is contained in:
@@ -2,7 +2,7 @@
|
|||||||
title: 隨機變數 (Random Variable)
|
title: 隨機變數 (Random Variable)
|
||||||
description:
|
description:
|
||||||
published: true
|
published: true
|
||||||
date: 2025-12-28T17:12:39.067Z
|
date: 2025-12-28T17:19:02.040Z
|
||||||
tags:
|
tags:
|
||||||
editor: markdown
|
editor: markdown
|
||||||
dateCreated: 2025-12-28T16:41:51.938Z
|
dateCreated: 2025-12-28T16:41:51.938Z
|
||||||
@@ -19,6 +19,9 @@ $0 \leq p_i \leq 1$ and $\sum_{p_i} = 1$
|
|||||||
Probability
|
Probability
|
||||||
$P(X = x) = p_i$
|
$P(X = x) = p_i$
|
||||||
|
|
||||||
|
Expectation
|
||||||
|
$E(X) = \sum_{i} p_i x_i$
|
||||||
|
|
||||||
### Cumulative Distribution Function (CDF)
|
### Cumulative Distribution Function (CDF)
|
||||||
|
|
||||||
$F(X) = P(X \leq x)$
|
$F(X) = P(X \leq x)$
|
||||||
@@ -31,9 +34,30 @@ Probabilistic properties of a continuous random variable.
|
|||||||
|
|
||||||
$\int f(x) \,dx\ = 1$
|
$\int f(x) \,dx\ = 1$
|
||||||
|
|
||||||
|
Expectation
|
||||||
|
$E(X) = \int xf(x) \,dx$
|
||||||
|
|
||||||
### Cumulative Distribution Function (CDF)
|
### Cumulative Distribution Function (CDF)
|
||||||
|
|
||||||
$F(X) = P(X \leq x) = \int_{-\infty}^{x} f(y) \,dy\\$
|
$F(X) = P(X \leq x) = \int_{-\infty}^{x} f(y) \,dy$
|
||||||
$f(X) = \frac{dF(x)}{dx}$
|
$f(X) = \frac{dF(x)}{dx}$
|
||||||
$P(a < x \leq b) = P(X \leq b) - P(X \leq a) = F(b) - F(a)$
|
$P(a < x \leq b) = P(X \leq b) - P(X \leq a) = F(b) - F(a)$
|
||||||
$P(a < x \leq b) = P(a \leq x \leq b)$
|
$P(a < x \leq b) = P(a \leq x \leq b)$
|
||||||
|
|
||||||
|
### Symmetric
|
||||||
|
If there is a point that,
|
||||||
|
$f(μ + x) = f(μ - x)$
|
||||||
|
Then,
|
||||||
|
$E(X) = μ$
|
||||||
|
Is the expectation of this random variable, equal to the point of symmetry.
|
||||||
|
|
||||||
|
### Median and Quantiles
|
||||||
|
The middle value of the random variable.
|
||||||
|
For median, set p to 0.5.
|
||||||
|
$F(X) = p$
|
||||||
|
|
||||||
|
### Variance
|
||||||
|
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.
|
||||||
|
|
||||||
|
$Var(X) = E(X^{2}) - (E(X))^{2}$
|
||||||
|
|||||||
Reference in New Issue
Block a user