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Lesson 6 of 20

Multiplication, Addition and Total Probability Rules

Addition Rule

The additional rule determines the probability of atleast one of the events occuring.

rule1
rule1

If A and B are mutually exclusive, then P(A and B) = 0, so the rule can be simplified as follows:

rule2
rule2

Multiplication Rule

Multiplication rule determines the joint probability of two events.

rule3
rule3

Joint probability of A and B is equal to the probability of A given B multiplied by the probability of B.

If A and B are independent, then P (A/B) = P (A)and the multiplication rule simplifies to:

rule4
rule4

Total Probability Rule

The total probability rule determines the unconditional probability of an event in terms of probabilities conditional on scenarios.

rule5
rule5

Let’s take an example to understand this.

Event A: Company X’s stock price will rise.

Event B: Inflation will fall. P(B) = 0.6. Therefore, probability of inflation not falling, P(BC) = 0.4

Probability of stock price rising given a fall in inflation, P(A|B) = 0.8

Probability of stock price rising given no fall in inflation, P(A|BC) = 0.6

We can use the total probability rule to calculate the probability of a rise in stock price as follows:

rule6
rule6

This is the total probability of event A occuring under all scenarios.

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Unconditional and Conditional Probabilities

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Joint Probability of Two Events

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Probability Concepts

20 lessons

Lessons

1
Probability - Basic Terminology
2
Two Defining Properties of Probability
3
Empirical, Subjective and Priori Probability
4
State the Probability of an Event as Odds
5
Unconditional and Conditional Probabilities
6
Multiplication, Addition and Total Probability Rules
7
Joint Probability of Two Events
8
Probability of Atleast One of the Events Occuring
9
Dependent Vs. Independent Events in Probability
10
Joint Probability of a Number of Independent Events
11
Unconditional Probability Using Total Probability Rule
12
Expected Value of Investments
13
Calculating Variance and Standard Deviation of Stock Returns
14
Conditional Expected Values
15
Calculating Covariance and Correlation
16
Expected Value of a Portfolio
17
Variance and Standard Deviation of a Portfolio
18
Bayes’ Theorem
19
Multiplication Rule of Counting
20
Permutation and Combination Formula

Quizzes

Probablity Concepts
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