Skip to Content
Cover Phong Tran
Phong Tran

Phong Tran

17 posts

Posts by Phong Tran

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

Consume the internet is too much Read more

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

Discrete Random Variables Read more

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

Bayes’ Theorem Read more

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(

Conditional Probability Read more