Chapter Overview
The chapter 'Probability' extends the basic concepts of probability covered in earlier classes. It focuses on conditional probability, independence of events, multiplication theorem, total probability theorem, Bayes’ theorem, and random variables. These concepts are vital for analyzing uncertain situations and making informed decisions based on data. Applications range across science, business, and social sciences.
Important Keywords
- Experiment: An operation that results in well-defined outcomes.
- Sample Space (S): The set of all possible outcomes.
- Event: A subset of the sample space.
- Conditional Probability: Probability of an event given that another event has already occurred.
- Independent Events: Events whose outcomes do not affect each other.
- Bayes’ Theorem: A method for finding a conditional probability when reverse probabilities are known.
- Random Variable: A function that assigns real numbers to outcomes of a random experiment.
Detailed Notes
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