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Phong Tran

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Consume the internet is too much

Now, my definition has changed for adaptation, and, to my research purposes and future ambition. I have to choose one, not balanced everything and my hobbies.

It has been a struggle since I got my Honours, I feel lucky for me to have the chance to work with the one whom I never seen or met or even work together before. And I felt that it is my honour and pleasure to work with them and they are my lifesaver from last year (not a disaster but a bad moment to look at it). I have to say each time

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Discrete Random Variables

Definition of Random variable

Decide an experiment random with S as sample space. A function X which assigns to every outcomes $s \in S$, a real number X(s) = x is called a random variable.

Example:

When we toss a coin. S the sample space {H, T}. Defining a random variable X as:

  • X(H) = 1 (if the result is heads)
  • X(T) = 0 (if the result is tails)

Definition: Discrete random variable and probability mass function.

A random variable called X, which is able to take on a countable number of values is a discrete random variable, which probability

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Bayes’ Theorem

Formula

$$ P(B|A) = \frac{P(A|B)P(B)}{P(A)} $$

Prove using conditional probability

$P(A|B) = \frac{P(A\cap B)}{P(B)}$, and, $P(B|A) = \frac{P(B\cap A)}{P(A)}$,$P(A\cap B)$same as $P(B \cap A)$

$$ P(A|B) \cdot P(B) = P(B|A) \cdot P(A) = P(A\cap B) $$ $$ P(A|B) \cdot P(B) = P(B|A) \cdot P(A) $$

Finally: $P(B|A) = \frac{P(A|B) \cdot P(B)}{P(A)}$

Defintion:

P(B) is the prior

P(A|B) is the likelihood

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Conditional Probability

Definition

When it comes to two events A and B, if P(B) > 0, then the probability of A given B is

$$ P(A|B) = \frac{P(A\cap B)}{P(B)} $$

Example

Rolling a dice with two events:

  • A: Outcomes is an even number
  • B: Outcomes is greater than 3

The sample space for rolling a dice is: $\{1,2,3,4,5,6\}$

  • Event A: $\{2,4,6\}$(even number)
  • Event B: $\{4,5,6\}$(greater than 3)
  • Intersection $A \cap B: \{4,6\}$(numbers that even and greater than 3)

Based on the formula of $P(

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