We learned about two approaches to probability theory in previous classes: (I) the Statistical approach and (ii) the Classical approach. Unfortunately, both theories have their shortcomings, as we will explore in this chapter.
A randomised experiment is one in which the results cannot be predicted or determined ahead of time. The sample space is the collection of all possible outcomes of an experiment. An event that is a subset of a sample space is linked to a random experiment. The empty set and the sample space S depict both impossible and definite events. The impossible event is referred to as intact, whereas the sure event is referred to as S, which refers to the whole sample space. A random experiment's outcome is known as a fundamental event. A complex event occurs when a single occurrence has several results. If the incidence of one event excludes the existence of the other, two events A and B in a sample space S are mutually exclusive. As a result, A and B can't happen simultaneously, therefore P (A B) = 0. If E1, E2,........, En are the n events of a sample space S, and E1 E2 E3........... En = S, then E1, E2,........ E3 are referred to as exhaustive encounters.
The chapter on probability has been brilliantly explained in the RD Sharma textbook, and there are a lot of questions to test a student's learning. One of the topics explained in this chapter is Random experiments. The chapter also talks about the sample spaces, events, algebra of events and various types of events. The chapter also includes the axiomatic approach to probability and additional theorems on probability.
Intending to assist students, experts have formulated comprehensive chapter-by-chapter strategies to help them grasp the principles quickly. RD Sharma Class 11 Maths Solutions have step-by-step instructions for all of the problems in Chapter 33, titled Probability. Experts have adopted the latest syllabus and have framed the solutions under the CBSE Board's exam pattern when designing the solutions.