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{ "item_title" : "Lecture Notes on Mathematical Probability Theory", "item_author" : [" Sanjay Ghevariya "], "item_description" : "Document from the year 2020 in the subject Mathematics - Stochastics, Sardar Patel University, language: English, abstract: Unlock the secrets of randomness and predictability with this essential guide to mathematical probability theory, a stepping stone to mastering advanced probabilistic concepts. Journey from the foundational principles of random variables, probability spaces, and distribution functions to the intricacies of joint distributions and the power of expectation. Delve into crucial inequalities that shape our understanding of probabilistic bounds, and explore the fascinating landscape of convergence, where different types of convergence for random variables reveal the underlying order in seemingly chaotic systems. Grasp the significance of the Strong Law of Large Numbers, a cornerstone theorem illuminating the relationship between sample averages and expected values. Discover the elegance and utility of characteristic functions, powerful tools for dissecting probability distributions, and master the inversion formula to unlock hidden distribution properties. Finally, confront the abstract beauty of weak convergence, a pivotal concept for analyzing the asymptotic behavior of random variables, paving the way for a deeper appreciation of the Central Limit Theorem, the crown jewel of probability theory. This book provides a rigorous yet accessible pathway for students and researchers alike, offering a comprehensive exploration of these fundamental concepts, making it an indispensable resource for anyone seeking a solid grounding in mathematical probability. Keywords: Random variables, probability space, distribution function, joint distribution, expectation, inequalities, convergence of random variables, strong law of large numbers, characteristic functions, inversion formula, weak convergence, central limit theorem. Prepare to embark on a transformative journey that will equip you with the essential tools and knowledge to tackle complex probabilistic chal", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/34/616/232/334616232X_b.jpg", "price_data" : { "retail_price" : "39.50", "online_price" : "39.50", "our_price" : "39.50", "club_price" : "39.50", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Lecture Notes on Mathematical Probability Theory|Sanjay Ghevariya

Lecture Notes on Mathematical Probability Theory

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Overview

Document from the year 2020 in the subject Mathematics - Stochastics, Sardar Patel University, language: English, abstract: Unlock the secrets of randomness and predictability with this essential guide to mathematical probability theory, a stepping stone to mastering advanced probabilistic concepts. Journey from the foundational principles of random variables, probability spaces, and distribution functions to the intricacies of joint distributions and the power of expectation. Delve into crucial inequalities that shape our understanding of probabilistic bounds, and explore the fascinating landscape of convergence, where different types of convergence for random variables reveal the underlying order in seemingly chaotic systems. Grasp the significance of the Strong Law of Large Numbers, a cornerstone theorem illuminating the relationship between sample averages and expected values. Discover the elegance and utility of characteristic functions, powerful tools for dissecting probability distributions, and master the inversion formula to unlock hidden distribution properties. Finally, confront the abstract beauty of weak convergence, a pivotal concept for analyzing the asymptotic behavior of random variables, paving the way for a deeper appreciation of the Central Limit Theorem, the crown jewel of probability theory. This book provides a rigorous yet accessible pathway for students and researchers alike, offering a comprehensive exploration of these fundamental concepts, making it an indispensable resource for anyone seeking a solid grounding in mathematical probability. Keywords: Random variables, probability space, distribution function, joint distribution, expectation, inequalities, convergence of random variables, strong law of large numbers, characteristic functions, inversion formula, weak convergence, central limit theorem. Prepare to embark on a transformative journey that will equip you with the essential tools and knowledge to tackle complex probabilistic chal

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Details

  • ISBN-13: 9783346162328
  • ISBN-10: 334616232X
  • Publisher: Grin Verlag
  • Publish Date: May 2020
  • Dimensions: 8.27 x 5.83 x 0.15 inches
  • Shipping Weight: 0.21 pounds
  • Page Count: 64

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