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{ "item_title" : "Probability", "item_author" : [" Mark Huber "], "item_description" : "This is an undergraduate textbook in probability aimed at math majors or for those intending to take courses such as mathematical statistics or stochastic processes. The book contains the content of a typical one-semester course for students with familiarity with calculus and linear algebra. The book also contains eight laboratory experiments using R. These can be used in class in place of lectures, or as supplemental activities for students.Topics include: basic probability definitions, conditional probability, Bayes' rule, the common distributions, densities, expectation, conditional expectation, joint densities, Bernoulli and Poisson point processes, covariance and correlation, counting measure, Lebesgue measure, Markov and Chebyshev tail inequalities, the Strong Law of Large Numbers, and the ever popular Central Limit Theorem.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/867/451/9798674518877_b.jpg", "price_data" : { "retail_price" : "69.99", "online_price" : "69.99", "our_price" : "69.99", "club_price" : "69.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Probability|Mark Huber

Probability : Lectures and Labs

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Overview

This is an undergraduate textbook in probability aimed at math majors or for those intending to take courses such as mathematical statistics or stochastic processes. The book contains the content of a typical one-semester course for students with familiarity with calculus and linear algebra. The book also contains eight laboratory experiments using R. These can be used in class in place of lectures, or as supplemental activities for students.Topics include: basic probability definitions, conditional probability, Bayes' rule, the common distributions, densities, expectation, conditional expectation, joint densities, Bernoulli and Poisson point processes, covariance and correlation, counting measure, Lebesgue measure, Markov and Chebyshev tail inequalities, the Strong Law of Large Numbers, and the ever popular Central Limit Theorem.

This item is Non-Returnable

Details

  • ISBN-13: 9798674518877
  • ISBN-10: 9798674518877
  • Publisher: Independently Published
  • Publish Date: August 2020
  • Dimensions: 10 x 7.99 x 0.94 inches
  • Shipping Weight: 2.19 pounds
  • Page Count: 362

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