Probability of Atleast One of the Events Occuring

This refers to the addition rule.

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

P (A or B) = P (A) + P (B) - P (A and B)

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

P (A or B) = P (A) + P (B) for mutually exclusive events A and B.

Example

An investor is contemplating buying one of the two stocks A or B. The probability P(A) that an investor will buy stock A is 0.30. The probability P(B) that the investor will buy stock B is 0.50. The probability that he may buy both P(A and B) is 0.10.

The probability that the investor will buy atleast one of the two stocks (A, or B, or both) is calculated as follows:

P(A or B) = 0.30 + 0.50 – 0.10 = 0.70

Suppose P(A) and P(B) are mutually exclusive events, that is, the investor will buy only one of the two stocks, then:

P(A or B) = 0.30 + 0.50 = 0.80

Related Downloads

Related Quizzes

Probablity Concepts

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $39 (Regular $57)
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.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.