Probability Theory Formulas
There are various formulas that are used in probability theory and some of them are discussed below,
- Theoretical Probability Formula: (Number of Favourable Outcomes) / (Number of Total Outcomes)
- Empirical Probability Formula: (Number of times event A happened) / (Total number of trials)
- Addition Rule of Probability: P(A ∪ B) = P(A) + P(B) – P(A∩B)
- Complementary Rule of Probability: P(A’) = 1 – P(A)
- Independent Events: P(A∩B) = P(A) ⋅ P(B)
- Conditional Probability: P(A | B) = P(A∩B) / P(B)
- Bayes’ Theorem: P(A | B) = P(B | A) ⋅ P(A) / P(B)
Read in Detail: Bayes Theorem
Probability Theory
Probability Theory: Probability is defined as the chance of happening or occurrences of an event. Generally, the possibility of analyzing the occurrence of any event concerning previous data is called probability. For example, if a fair coin is tossed, what is the chance that it lands on the head? These types of questions are answered under probability.
Probability measures the likelihood of an event’s occurrence. In situations where the outcome of an event is uncertain, we discuss the probability of specific outcomes to understand their chances of happening. The study of events influenced by probability falls under the domain of statistics.
Table of Content
- What is Probability Theory in Maths?
- Real-Life Example of Probability – Flipping a Coin
- Probability Theory Definition
- Theoretical and Experimental Probabilities
- Theoretical Probability
- Experimental Probability
- Probability Theory Examples
- Basics of Probability Theory
- Random Experiment
- Sample Space
- Event
- Random Variable
- Discrete Random Variable
- Continuous Random Variable
- Probability Theory Formulas
- Probability Theory in Statistics
- Applications of Probability Theory
- Solved Examples on Probability Theory
In this article, we will learn about, Probability theory, its formulas, examples, applications, and others in detail.