Unconditional Probability Using Total Probability Rule

As we learned earlier, the total probability rule determines the unconditional probability of an event in terms of probabilities conditional on scenarios.

P(A) = P(A | S1)P(S1) + P(A | S2)P(S2) + … + P(A | Sn)P(Sn)

Where the scenarios S1, S2, …Sn are mutually exclusive and exhaustive.

Let’s take one more example of the Total Probability Rule.

An analyst is assessing the performance of a stock under different scenarios. He comes up with the following probabilities.

State of EconomyProbability of Economic StateStock PerformanceProbability
No recession P(RC)0.60Rise P(SR | RC)0.70
Fall P(SRC | RC)0.30
Recession P(R)0.40Rise P(SR | R)0.20
Fall P(SRC | R)0.80

Question 1

Based on the above data, what is the total probability of a stock rise? We need to find the unconditional probability of a stock rise under all scenarios.

P(SR) = P(SR | RC) P(RC) + P(SR | R) P(R)

\= 0.70*0.60 + 0.20*0.40 = 0.5

Question 2

What is the joint probability of having a recession and at the same time having a stock price fall?

P(R and SRC) = P(SRC | R)x P(R) = 0.8*0.4 = 0.32

Related Downloads

Related Quizzes

Probablity Concepts
Membership
Learn the skills required to excel in data science and data analytics covering R, Python, machine learning, and AI.
I WANT TO JOIN
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Saylient AI Logo

Take the Next Step in Your Data Career

Join our membership for lifetime unlimited access to all our data analytics and data science learning content and resources.