Which are the important topics for the Probability chapter in NDA Maths paper?

<p>Here you can refer to the important topics for the Probability chapter in the NDA Maths paper:</p><p>Basic Concepts of Probability:</p><ul><li>Definition of Probability (Classical and Statistical)</li><li>Sample Space and Events</li><li>Types of Events (Simple, Compound, Independent, Dependent, Exhaustive, Mutually Exclusive)</li><li>Venn Diagrams (for representing events)</li></ul><p>Theorems of Probability:</p><ul><li>Addition Theorem for Disjoint Events</li><li>Conditional Probability and Bayes' Theorem (simple problems)</li></ul><p>Random Variables and Probability Distributions (basic understanding):</p><ul><li>Definition of Random Variable</li><li>Types of Random Variables (Discrete &amp; Continuous)</li><li>Introduction to Probability Distributions (concept, not solving complex problems)</li></ul><p>Simple Problems on:</p><ul><li>Finding the probability of an event (using various methods)</li><li>Applying theorems like Addition theorem and Bayes' theorem</li><li>Conditional probability</li></ul><p>&nbsp;</p>

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<p>NDA Maths question paper carries questions from Arithmetic, Mensuration, Algebra, Geometry, Trigonometry, Statistics, etc. Matrices and Determinants. This paper carries 120 questions and total marks allotted to Maths section are 300. The important topics for the Probability chapter in NDA Maths paper are Random experiment, outcomes, and associated sample space, events, mutually exclusive and exhaustive events, impossible and certain events. Union and Intersection of events. Complementary, elementary, and composite events. Definition of probability&mdash;classical and statistical&mdash;examples. Elementary theorems on probability-simple problems. Conditional probability, Bayes&rsquo; theorem&mdash;simple problems. Random variable as function on a sample space. Binomial distribution, examples of random experiments giving rise to Binomial distribution.</p>

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<p>The important topics for the Probability chapter in NDA Maths paper are Probability: Random experiment, outcomes, and associated sample space, events, mutually exclusive and exhaustive events, impossible and certain events. Union and Intersection of events. Complementary, elementary, and composite events. Definition of probability&mdash;classical and statistical&mdash;examples. Elementary theorems on probability-simple problems. Conditional probability, Bayes&rsquo; theorem&mdash;simple problems. Random variable as function on a sample space.&nbsp;Binomial distribution, examples of random experiments giving rise to Binomial distribution.</p>

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